Download Antimicrobial Pharmacokinetics and Pharmacodynamics

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Psychedelic therapy wikipedia , lookup

Discovery and development of non-nucleoside reverse-transcriptase inhibitors wikipedia , lookup

Plateau principle wikipedia , lookup

Psychopharmacology wikipedia , lookup

Biosimilar wikipedia , lookup

Neuropharmacology wikipedia , lookup

Drug design wikipedia , lookup

Medication wikipedia , lookup

Discovery and development of cephalosporins wikipedia , lookup

Pharmaceutical industry wikipedia , lookup

Prescription costs wikipedia , lookup

Drug discovery wikipedia , lookup

Neuropsychopharmacology wikipedia , lookup

Drug interaction wikipedia , lookup

Bad Pharma wikipedia , lookup

Pharmacogenomics wikipedia , lookup

Pharmacognosy wikipedia , lookup

Theralizumab wikipedia , lookup

Pharmacokinetics wikipedia , lookup

Bilastine wikipedia , lookup

Transcript
Antimicrobial
Pharmacokinetics and
Pharmacodynamics
DAVID ANDES, MD
The goal of antimicrobial therapy is to effectively eradicate pathogenic organisms
while minimizing drug toxicities. Various factors affect the treatment outcomes of
infectious diseases including host defense mechanisms, the site of infection, the virulence of the pathogen, and the pharmacologic properties of the antimicrobial agent
used to treat the infection. The factor under the greatest control of the clinician, however, is related to the choice and dosing of antimicrobial agents. Various pharmacologic factors govern the design of an optimal antimicrobial regimen. These factors are
conventionally divided into two distinct components: (1) pharmacokinetics and
(2) pharmacodynamics. Examination of pharmacokinetic and pharmacodynamic relationships have been undertaken for most antibacterial drug classes and more recently
for a number of antifungal and antiviral drug classes. These analyses are being recognized as increasingly important in the design of optimal antimicrobial therapies.
ANTIMICROBIAL PHARMACOKINETICS
Pharmacokinetics deals with drug disposition in the body, including the absorption,
distribution, and elimination of drugs. It is these factors that determine the time course
of drug concentrations in serum and tissues for a given dosing regimen. With antimicrobial agents one is particularly concerned about concentrations at the site of
infection.
Kinetics at Site of Infection
Many studies have attempted to correlate antibiotic concentrations in serum with those
in various tissues or sites of infection. However, several problems arise in both the
measurement and the interpretation of drug concentrations in tissues. In theory, tissue
concentrations consist of vascular, interstitial, and intracellular compartments.
Different antimicrobial agents can vary in their ability to accumulate within these three
compartments. Because most infections occur in tissues and the common pathogens
are extracellular, interstitial fluid concentrations at the site of infection should be the
prime determinants of efficacy. Free-drug concentrations in serum are a much better
surrogate of interstitial fluid concentrations than are tissue homogenate concentrations.
The majority of studies, however, have used tissue homogenates to determine antibiotic concentrations in tissue." The relative distribution of an antibiotic within a tissue
sample cannot be distinguished by this method. Tissue homogenates mix interstitial,
intracellular, and vascular components together. Measurement of antibiotic concentrations in tissue homogenate tends to underestimate or overestimate interstitial fluid
concentrations depending upon the ability of the antimicrobial to accumulate
2 I Antimicrobial Pharmacokinetics and Pharmacodynamics
intracellularly. For example, one would expect that antibiotics with poor intracellular penetration, such as the (3lactams, would reach high concentrations in interstitial
fluid. However, tissue homogenate methods suggest this
class of drugs penetrates poorly into the interstitial space
because of the dilution of samples with intracellular contents. Techniques that directly extract interstitial fluid,
such as subcutaneously implanted cotton threads or more
recently microdialysis methods, demonstrate high (3-lactam concentrations in this tissue compartment that are
similar to free drug levels in senum. 3-s
On the other hand, since fluoroquinolones accumulate
intracellularly, tissue homogenates can overestimate the
concentration of drug in interstitial fluid. Not all
pathogens, however, are located in the extracellular space.
For example, pathogens such as Legionella spp. and
Chlamydia spp. reside primarily in the intracellular space.
One may then anticipate superior quinolone potency in
the treatment of these infections. However, when one
looks at the relationship between the amount of fluoroquinolone necessary for efficacy in the treatment of both
intracellular and extracellular pathogens, no difference is
seen (Fig. 1-1). 6 This may suggest that only a fraction of
the amount of quinolone that is intracellular is available
for antimicrobial activity. Furthermore, it is clear that not
all drugs that accumulate intracellularly do so in similar
intracellular compartments. For example, fluoroquinolones reside in the cytosol, whereas macrolides concentrate in phagolysosomes. 7 In the same manner, not all
intracellular pathogens have the same subcellular distribution. Legionella spp. and Chlamydia spp. are found in
100
0
00
80
O Intracellular
0 Extracellular
•a•a 4b
00
80
SD
40
8•
%&(D
9h
20
O
0
Oft)•a7
3
10
30
100
300
1000
24 hour AUC/MIC ratio
Relationship between the 24-hour area under the concentration curve (AUC)-to-minimum inhibitory concentration (MIC)
ratio and mortality for extracellular (hollow circles) and intracellul ar (solid circles) pathogens in various experimental infection
models in mice, rats, and guinea pigs treated with fluoroquinolones. (From Craig WA, Dalhoff A: Pharmacodynamics of fluoroquinolones in experimental animals. In Kuhlman J, Dalhoff A,
Zeiler HJ, [eds]: Handbook of Experimental Pharmacology, vol 127:
Quinolone Antibacterials. pp 207-232.)
FIGURE 1-1.
phagosomes, Listeria and Shigella are found in the
cytosol, and Salmonella in phagolysosomes. 7
Although for most antibiotics it appears that serum concentrations serve as an adequate surrogate of concentrations
at the site of infection, there is growing controversy in
regard to certain classes of compounds in the treatment of
lower respiratory tract infections. For a few antimicrobial
classes there is a large discrepancy between serum drug
levels and levels in epithelial lining fluid (ELF). ELF is the
fluid that bathes the respiratory epithelium, where it is
believed most pathogens in bacterial pneumonia reside. For
drugs such as clarithromycin and azithromycin, ELF concentrations can be 10- to 20-fold higher than in serum
(Table 1-1)."° Some investigators suggest that for drugs
with this degree of kinetic difference, the pharmacokinetics
in ELF may be better for predicting therapeutic outcomes
than those in serum. However, at this time there have not
been either animal model or clinical trial data supporting or
disproving this hypothesis.
Impact of Protein Binding
Various pharmacologic factors can alter the activity of an
antimicrobial agent. In some circumstances, protein binding can have a detrimental effect, whereas in others it
may enhance dosing efficacy. The antimicrobial activity
of a drug is inversely related to the extent of protein binding. Protein binding of antimicrobials in serum can interfere with biologic activity, restrict tissue distribution, and
delay elimination." , " For example, a drug such as
phenylbutazone, known to displace penicillins from albumin-binding sites, enhances its in vitro antimicrobial
activity because it is only the unbound antimicrobial fraction that is available for penetration to the site of
infection for antimicrobial activity. 13 In spite of numerous investigations documenting these effects, the clinical
significance of protein binding remains controversial.
A common inaccurate assumption is that a given
degree of protein binding will exert a similar pharmacologic effect on all antimicrobials. On the contrary, the
effects of drug protein binding on the pharmacokinetics
of an antimicrobial depend on how it is eliminated by the
body. Excretion of drugs into the urine occurs either by
glomerular filtration or tubular secretion. Protein binding
reduces the rate of elimination only of drugs cleared by
glomerular filtration. In contrast, tubular secretion is
largely independent of protein binding. The diverging
effects of binding on drugs depending upon their route of
elimination is further illustrated in Fig. 1-2, which
graphs the area under the serum concentration time curve
(AUC) of both total and free levels of 16 R-lactams in
serum and skin blister fluid based upon the degree of protein binding." In the left panel, one can see that the effect
of increasing binding for drugs eliminated by tubular
secretion is a progressive decline in free drug AUC in
both serum and blister fluid. On the other hand, for the
compounds eliminated by glomerular filtration the right
Antimicrobial Pharmacokinetics and Pharmacodynamics 13
TABLE 1-1 m Comparison of Clarithromycin and Azithromycin Kinetics in Serum
and ELF
Clarithromycin
Azithromycin
Time (hours)
Serum (gg/ml)
ELF (gg/ml)
Serum (gg/ml)
ELF (lag/ml)
4
8
12
24
24-h AUC
2.0
1.6
1.2
0.2
25
34.5
26.1
1 5.1
4.6
391
0.08
0.09
0.04
0.05
1.3
1.0
2.2
1.0
1.2
28
ELF, epithelial lining fluid.
AUC, area under the serum concentration-time curve;
panel demonstrates the progressive rise in AUC for total
drug and the relatively constant AUC of free drug over a
wide range of binding. The effect of protein binding on
drugs with primarily hepatic elimination is less clear. If
the drug has a low hepatic extraction ratio, however, the
effect of protein binding would tend to slow elimination.
On the other hand, for drugs with high extraction ratios,
protein binding would affect elimination very little.
For drugs eliminated predominantly by tubular secretion
or rapid hepatic extraction, the peak senun concentration
level (C.), the AUC, and the duration of time the serum
levels exceed the minimum inhibitory concentration (1VIIC)
expressed as the percentage of the dosing interval (T >MIC)
of highly bound drugs would be reduced by high protein
binding. One might predict that binding of greater than 80%
would be necessary to reduce unbound free drug levels in
the body enough to adversely affect antimicrobial activity.
For example, in a Staphylococcus aureus murine peritonitis
model seven penicillin antibiotics with similar in vitro activity and pharmacokinetic profiles (all eliminated by tubular
secretion) with the exception of protein binding were evaluated. The amount of drug necessary to cure 50% of the
mice was directly related to the degree of protein binding. 12
The higher the binding, the larger the total dose required.
For drugs eliminated predominantly by glomemlar filtration, increasing binding reduces the peak level of free
drug, but has no major effect on the AUC, and prolongs the
duration of time free drug levels would exceed the MIC of
sensitive organisms. Thus, if peak level was the important
determinant of efficacy, protein binding might have a detrimental effect. On the other hand, if the duration of time
serum levels exceeded the MIC were important, higher protein binding could have a beneficial effect. 14
Pharmacokinetic Impact of Dosing
Regimen Design
The pharmacokinetic parameters that characterize the
time course of antibiotic concentration in serum and at
sites of infection include several measures of exposure
including the AUC, C. X, and the T >MIC (Fig. 1-3).
When a drug's half-life is constant, each of these kinetic
parameters will change with the dose magnitude and the
frequency of drug administration. For a given total daily
dose of drug the 24-hour AUC will be relatively constant
regardless of the dosing regimen. Administration of large
infrequent doses will result in high peak concentrations
and shorter duration of time serum levels exceed a
1000
Secreted drugs
500
200
100
50
FIGURE 1-2. Relationship of the area under the concentration curve of total and free drug in serum and
free drug in blister fluid with the percentage of protein bound drug for 16 R-lactams. Drugs eliminated
primarily by secretion are shown in the left panel and
those eliminated primarily by filtration are shown in
the right panel. (From Craig WA, Suth B: Protein
binding and the antimicrobial effects: Methods for
the determination of protein binding. In Lorian V [ed]:
Antibiotics i n Laboratory Medicine, 4th ed.
Baltimore, Williams & Wilkins,1996, pp 367-402.)
25
10
0-• Total drug in serum
0-0 Free drug in serum
-', -A Free drug in blister fluid
5
2.5
0
1 LL
0
a
20
40
60
80 100 0
20
Protein binding (%)
40
60
80
100
4 I Antimicrobial Pharmacokinetics and Pharmacodynamics
The use of the MIC and MBC as predictors of antimicrobial success has led to two erroneous generalizations
in dosing regimen design. One is that to achieve an optimal effect, drug concentrations must exceed the MIC for
most of the dosing interval to prevent organism regrowth.
Another dosing generalization has been that an increase
in concentrations will invariably enhance antimicrobial
efficacy.
c
0
Time
FIGURE 1-3. Antimicrobial pharmacokinetic parameters in relation to
the minimum inhibitory concentration (MIC). AUC, area under the
concentration curve.
threshold value such as the MIC. The converse will occur
with lower drug doses administered more frequently.
PRE-PHARMACODYNAMIC DOSING TRADITIONS
Traditionally antimicrobial dosing regimens have been
deduced from the relationship between some measure of
drug potency in vitro such as the MIC or minimum bactericidal concentration (MBC) of an antimicrobial agent
for important pathogens and the pharmacokinetics of the
drug in serum. These parameters do not provide information regarding the time course activity of drugs, however.
For example, the MIC does not provide information on
the effect of fluctuating drug concentrations characteristically encountered in a patient, or on whether there are
antimicrobial effects that can persist after drug exposure.
Furthermore the MBC does not reveal the effect that
higher drug concentrations have upon the extent or rate of
killing. The persistent suppression of organism growth or
regrowth after short antimicrobial exposures has been
called the postantibiotic effect. 15 The effect of increasing
concentrations upon the activity of an antimicrobial and
the presence or absence of prolonged antimicrobial
effects persisting after drug exposure give a much better
description of the time course of activity than provided
by the MIC or MBC.
PHARMACOKINETICS
ANTIMICROBIAL PHARMACODYNAMICS
Pharmacodynamics examines the relationships between
the antimicrobial and organism over time (time course of
activity), determining the effects of variations in drug
kinetics on treatment outcomes. Various studies have
demonstrated that the success of a drug and dosing regimen is dependent upon a measure of drug kinetics and a
measure of drug potency against the infecting organism
(e.g., MIC or MBC) (Fig. 1-4). Kinetic parameters, such
as the C./MIC ratio, 24-hour AUC/MIC ratio, and time
above MIC, have been shown to be major determinants
of antimicrobial efficacy. Furthermore, studies examining the relationship between in vitro measurements (MIC
and MBC) and the time course activity of various antimicrobials have demonstrated that drugs with different
mechanisms of action vary in respect to the effect of
increasing drug concentrations. These pharmacokinetic
and pharmacodynamic analyses provide a better understanding of the relationship between drug dosing and
effect. Understanding these relationships for various
antimicrobial classes has proven valuable for (1) the
design of appropriate dosing regimens in the treatment
for both susceptible and multiply resistant pathogens, (2)
the development of in vitro susceptibility breakpoints,
and (3) the understanding how antimicrobial dosing
relates to the emergence and spread of drug resistance.
Pharmacodynamic Determinants of Efficacy
The time course of antimicrobial activity is dependent on the drug's pharmacokinetics and two major
PHARMACODYNAMICS
Absorption
Distribution
Elimination
Antimicrobial
dosing
regimen
Time course
concentration in
serum
Time course
concentration in
tissues
Pharmacologic
and toxicologic
effect
Time course
concentration at
site of infection
Antimicrobial
effect
FIGURE 1-4. Overview of pharmacokinetics and pharmacodynamics in antimicrobial therapy. (From Craig WA: Pharmacokinetic/pharmacodynamic Parameters: Rationale for antibacterial dosing of mice and men. Clin Infect Dis 1998;26:1-12.)
Antimicrobial Pharmacokinetics and Pharmacodynamics 1 5
pharmacodynamic characteristics. The first is the rate of
organism killing and whether increasing drug concentrations enhances the rate and extent of killing. The second is the absence or presence of inhibitory effects on
organism growth that persist after drug levels have
fallen below the MIC.
Concentration-Dependent vs. Time-Dependent Killing
it is clear that progressive escalation of antimicrobial
concentrations above the MIC will not enhance organism
killing for all antimicrobial drug classes. For example,
the killing activity of the R-lactams, macrolides, glycopeptides, clindamycin, tetracyclines, oxazolidinones,
triazoles, and flucytosine is saturable with respect to the
effect of drug concentration upon the rate and extent of
killing. 16-24 Maximal in vitro killing with (3-lactam compounds is usually observed at concentrations four to eight
times the MIC. 11,21 Higher concentrations do not enhance
drug activity and in fact have been demonstrated to be
less active in some models (Eagle effect). 26 For agents
with saturable killing with respect to drug concentration
it is important to maximize the duration of time for which
concentrations exceed the MIC rather than to enhance
intensity of drug exposure.
On the other hand, there are a number of antimicrobial classes that do demonstrate concentration-dependent
organism killing. With these drugs, higher concentrations
result in more rapid and extensive organism killing.
These killing characteristics have been observed with the
aminoglycosides, fluoroquinolones, metronidazole,
ketolides, the lipopeptide daptomycin, amphotericin B,
and the new echinocandin class of antifungal. 6,15,1s,19,27-31
The pharmacologic goal of dosing regimens with these
agents would be to maximize concentrations by administering the total daily dose infrequently.
Persistent Effects
Prolonged persistent effects are due to various phenomena referred to as postantibiotic effects (PAE), postantibiotic sub-MIC effects, and postantibiotic-leukocyte
effects. 15,25,32-34 Sub-MIC concentrations of a number of
antimicrobial classes have been shown to inhibit organism growth. 35 Sub-MIC concentrations can also prolong
the duration of the PAR The postantibiotic leukocyte
effect refers to the observation that organisms that have
been exposed to antimicrobials are more susceptible to
phagocytosis by leukocytes. This phenomenon can also
prolong the duration of the PAR Persistent suppression
of growth after limited exposure was initially reported in
the 1940s with penicillin. 26 These phenomena have since
been demonstrated both in vitro and in animal infection
models for nearly all classes of antimicrobials. 11,21 Nearly
all antibacterials appear to be capable of producing persistent effects with staphylococci. For example, although
Cefazolin serum levels in mice remained above the MIC
for only 1.6 hours, the growth of S. aureus in the thighs
of treated animals was inhibited for several hours longer
25
-0 -•-
Control growth
Cefazolin 12.5 mg/kg
-+~- Cefazolin serum levels
.c
rn
t
10
tT
8
E
U
0
0
J
MIC 1.6
7
Above
MIC
PAE = 4 hr
2.5
1
6
E
N
fn
0.5
Time (hours)
FIGURE tom. Cefazolin in vivo postantibiotic effect (PAE) with Staphylococcus aureus (American Type Culture Collection) (ATCC) 25923 in
neutropenic murine thigh infection model following a 12.5 mg/kg
dose. Hollow circles represent mean control in thighs from 3 mice.
Solid circles, growth in thighs of treated animals. Simultaneous
serum cefazolin concentrations are also shown. CFU, colony-forming
units; MIC, minimum inhibitory concentration. (From Craig WA,
Gudmundsson S: Postantibiotic effect In Lorian V [ed]: Antibiotics in
Laboratory Medicine, 4th ed. Baltimore, Williams & Wilkins,1996, pp
296-329.)
(PAE 4 hours) (Fig. 1-5). 11 However, drugs that inhibit
protein or nucleic acid synthesis such as the aminoglycosides, fluoroquinolones, tetracyclines, and rifampin also
produce prolonged PAEs with gram-negative bacilli and
streptococci. 11,25 In contrast, (3-lactams produce short or
no PAEs with gram-negative bacilli. The only exception
is with the carbapenems, primarily with strains of
Pseudomonas aeruginosa.
Antifungal compounds have also been shown to have
prolonged persistent effects. The most pronounced
effects have been observed with the polyenes such as
amphotericin B.2' The triazole compounds have not
demonstrated PAEs in vitro but have demonstrated prolonged effects in vivo, probably representing significant
postantifungal sub-MIC effects . 10,16,17 The pyrimidine
analog flucytosine has been found to produce only modest persistent effects. 16 The new echinocandin class has
also demonstrated prolonged in vitro PAEs .3o
The clinical significance of the pharmacodynamic
observation of prolonged persistent effects following a
limited drug-organism interaction is related to the poten
tial to lengthen dosing intervals. If organism growth
remains suppressed after drug levels fall below the MIC,
then the dosing interval could be lengthened until the
beginning of organism regrowth or the end of the PAE.
Patterns of Activity
On the basis of these two time-course characteristics
(effects of increasing drug concentrations and persistent
effects), three patterns of antimicrobial activity have been
observed. The first pattern of activity is characterized by
marked concentration-dependent killing over a wide
61
s
t
v0
J
Antimicrobial Pharmacokinetics and Pharmacodynamics
I n vitro time-kill curves for
against Pseudomonas
aeruginosa at escalating multiples of
the minimum inhibitory concentration
( MIC) (left pane4 and bacterial counts
of the same organism in vivo in neutropenic mice following single doses of
tobramycin administered subcutaneously. Tobramycin MIC, 0.5 gg/mL.
CFLJ, colony-forming units; PAE, postantibiotic effect. (From Craig WA,
Gudmundsson S: Postantibiotic effect.
I n Lorian V [ed]: Antibiotics in
Laboratory Medicine, 4th ed. Baltimore,
Williams & Wilkins,1996, pp 296-329.)
FIGURE 1-6.
tobramycin
-0-
Control
__O
/~ - 1 X MIC
4 X MIC
- A - 16XMIC
-¢ 64 X MIC
U
0
of
0
J
Time (hours)
range of concentrations and prolonged persistent effects.
The higher the drug concentration, the greater the extent
and rate of organism killing. This is illustrated in Fig. 1-6,
where the activity of tobramycin against P. aeruginosa is
examined in vitro and in vivo." In the left panel are seen
marked concentration-dependent killing over a wide
range of in vitro concentrations. In the right panel one
can observe the prolonged dose-dependent growth suppression (PA-Es) in vivo. This pattern of killing and persistent growth suppression is observed with the
aminoglycosides, fluoroquinolones, metronidazole, the
ketolides, daptomycin, and the polyene antifungals.6,18,24,27,29,3911 Since higher doses will lengthen the
duration of antimicrobial effects, large infrequent doses
of these agents maximizing the C./MIC ratio could
enhance their activity. Furthermore, the prolonged persistent effects allow doses to be spread apart because
organism regrowth will be suppressed when levels fall
below the MIC.
The second pattern of activity is characterized by a
saturation of the rate of killing at concentrations near the
MIC and minimal-to-modest persistent effects. Thus high
concentrations will not kill the organisms faster or more
extensively than low concentrations. The duration of
exposure rather than concentration is the major determinant of the extent of killing. This pattern of activity is
called time-dependent killing and is the pattern that characterizes the activity of all of the (3-lactam antibiotics,
most of the macrolides, clindamycin, the oxazolidinones,
and flucytosme. 15-17,19,20,23,24,4013 For example, Figure 1-7
shows experimental data from both an in vitro and in vivo
infection model with P. aeruginosa examining the activity of the P-lactam, ticarcillin. 38 In both the in vitro and in
vivo studies, concentrations above four times the MIC
did not appreciably increase the rate of killing.
Furthermore, regrowth of organisms in vivo began immediately after serum levels dropped below the MIC (no
persistent effect). With these drugs the frequency of
administration and the dose are both important determinants of efficacy. Time above the MIC has been the major
pharmacokinetic-pharmacodynamic (PK-PD) parameter
correlating with efficacy of these drugs.
The final pattern of activity is not only characterized
by time-dependent killing but also by prolonged persistent effects. This unique pattern of activity characterizes
the azalide azithromycin, the tetracyclines, glycopepfdes, streptogramins, and the tfazole antifungals. 1,19,16
The dosing frequency is usually not a major factor in
determining the efficacy of these drugs. The 24-hour
AUC/MIC ratio is the primary parameter correlating with
in vivo efficacy because the prolonged persistent effects
prevent time above MIC from becoming important.
sL
0
1-7. I n vitro ti me-kill
curves for ticarcillin against
Pseudomonas aeruginosa at escal ating multiples of the minimum
i nhibitory concentration (MIC) (left
panes and bacterial counts of the
same organism in vivo in neutropenic mice following single
doses of ticarcillin administered
subcutaneously. Ticarcillin MIC,16
gg/mL. CFU, colony-forming units;
PAE, postantibiotic effect.
FIGURE
J
E:
uU
0
-o-- Control
m
0
J
F- 300 mg/kg PAE 0.6 hr
--D-- 600 mglkg PAE 1.9 hr
-11-- 2400 mglk9 PAE 0.6 hr
Time (hours)
Antimicrobial Pharmacokinetics and Pharmacodynamics 1 7
16
8
c
0
a
W
4
c
Effect of increasing the dose or
changing the dosing interval of a hypothetical
drug on the C.. ), -to-minimum inhibitory concentration (MIC) ratio, area under the concentration
curve (AUC)/MIC ratio, and the duration of time
that serum levels exceed the MIC. (From Craig
WA: Pharmacokinetic/pharmacodynamic parameters: Rationale for antibacterial dosing of mice
and men. Clin Infect Dis 1998;26:1-12.)
FIGURE 1-8.
2
U
1
E
2
m
0.5
0.25
0.125
0
2
4
6
8
0
2
4
6
Time (hours)
given every 8 hours, resulting in a lower C. level but a
higher T >MIC. Over each 24-hour treatment regimen
period the AUC/MIC ratio of the two regimens would be the
same. With few exceptions, such study designs are most
often not possible in human trials but are easily undertaken
in animal infection models.
A study performed in the 1970s by Bodey et al did,
however, vary dosing frequency comparing the efficacy
of continuous vs. intermittent infusions of various antibiotics, including cefamandole, in febrile neutropenic
patients." For those patients infected with susceptible
pathogens, continuous infusion was more efficacious
than intermittent administration. Two other studies have
compared continuous and intermittent infusions of ceftazidime in the treatment of gram-negative infections. 45,46
These investigations found equivalent outcomes despite
the fact that less total drug was used for continuous infusion (3-4 g vs. 6 g, respectively). Both dosing regimens,
however, provided concentrations that exceeded the MIC
for virtually all of the dosing interval.
Although it can be difficult to vary dosing regimens
in clinical trials enough to reduce the inherent parameter
interrelationships, studies in animal infection models do
allow dosing regimen design to eliminate much of the
parameter interdependence. As shown in Figure 1-9,
DETERMINATION OF PHARMACOKINETICPHARMACODYNAMIC PARAMETERS
PREDICTING EFFICACY
The specific parameters most commonly correlated with
antimicrobial treatment outcome include the CmWC
ratio, the 24-hour AUC/MIC ratio, and the T >MIC. These
relationships have been examined primarily in in vitro and
in vivo infection models. Investigation in human clinical trials to support or refute the observations from in vitro and
animal models can be difficult because of the design of most
clinical trials. Most studies are designed to determine the
impact of higher doses of drug on efficacy with usually all
regimens using the same dosing interval. As illustrated in
the left panel of Figure 1-8, a four-fold higher dose results
./IVIIC ratio, a higher AUCMIIC ratio, and a
in a higher Cm
longer duration of time above MIC. If a higher dose is associated with a better therapeutic outcome, it is difficult to
determine which parameter is of primary importance, as all
three increase to a similar extent. However, much of the
interdependence among pharmacodynamic parameters can
be eliminated with dosing regimens that use different dosing
intervals. In the right panel of Figure 1-8 a dose administered every 2 hours is compared to a four-fold higher dose
1000
R2 - 99%
R2 - 76%
R2 = 50%
O
U_
O
OO
O
100
O
U
Q
O
O
O
10
0
O
4
6
O
8 10 12 14 16 18 20 0
10
15
O
010
Three dosing intervals
Two dosing intervals
5
O
08
00
Single dosing interval
2
O
O
20 25 30 35
0
20
40
60
80
100
T>MIC
I nterrelationship among dosing interval number and the pharmacokinetic and pharmacodynamic parameters. AUC, area under
the concentration curve; MIC, minimum inhibitory concentration; Rz, percentage of variation in bacterial numbers that could be attributed
to differences in each of the pharmacodynamic parameters; T > MIC, percentage of time serum concentrations exeed the MIC.
FIGURE 1-9.
8 1 Antimicrobial Pharmacokinetics and Pharmacodynamics
o
&&$~ -e0
0 0
0
$0
0I
0
20
40
60
80
3
Time above MIC (%)
30
300
3000
3
24-hour AUC/MIC
30
8
300 3000
omax/MIC
with only a single dosing interval (frequency) there is a
strong correlation between the AUC/MIC ratio and the
T >MIC. With two dosing intervals the interrelationship
is less significant and is even less so with three or more
dosing intervals. In these experimental designs, several
total daily doses and dosing intervals are used to vary the
drug AUC, Cmax, and T >MIC. Subsequent analysis of
treatment endpoints in relation to each of the parameters
then allows one to determine which parameter(s) best
predicts antimicrobial activity.
Time above the MIC has consistently been the only
PK-PD parameter that correlates with the efficacy of the
(3-lactams.I I For example, Leggett et al demonstrated that
the cumulative dose of several (3-lactams necessary to produce 50% of the maximum bacteriologic effect (ED 50)
increased significantly with longer dosing intervals. 21 In
similar animal infection models, others have found continuous R-lactam infusion regimens to be more efficacious
than those intermittently dosed. " Figure 1-10 illustrates
the relationship between the treatment efficacy of the carbapenem meropenem against P. aeruginosa and each of
the pharmacokinetic (PK) and pharmacodynamic (PD)
parameters. Pairs of neutropenic mice were treated with
multiple dosage regimens of meropenem that varied both
in the total dose and dosing interval. Changes in organism
burden after 24 hours of therapy are correlated with the
C m./MIC ratio, the 24-hour AUC/MIC ratio, and the
percentage of time that serum levels exceed the MIC.
Regression of the data with both the AUC/MIC ratio (coefficient of determination = R2 = 62%) and the Clna,,/MIC (R2
= 41 %) demonstrate only a modest relationship. However,
regression in the percentage of time serum levels remain
above the MIC (R2 = 89%) demonstrates a strong relationship. Time above the MIC is also the parameter that correlates with the efficacy of most of the macrolides,
clindamycin, oxazolidinones, and flucytosine. 16,17,19,20
For aminoglycosides, fluoroquinolones, ketolides,
streptogramins, glycopeptides, daptomycin, azithromycin,
amphotericin B, and fluconazole the AUC/MIC or
Cma
./MIC ratio has been the parameter that correlate with
efficacy in animal infection models.` Figure 1-11 demonstrates the relationship between levofloxacin efficacy and
each of the PK and PD parameters in a neutropenic
murine thigh infection model due to Streptococcus pneumoniae. The strongest parameter correlation is seen
with the 24-hour AUC/MIC ratio (AUC/MIC R2 = 88%,
T >MIC R2 = 50%, C../MIC R2 = 45%). Several other
studies have demonstrated the importance of the concentration-dependent PK and PD parameters for these
drugs 12,13 For example, Blaser et al demonstrated superior
efficacy with single compared with multiple aminoglycoside and quinolone exposures, suggesting that achieving a
high peak concentration is important 2' These observations
from both in vitro and in vivo models have demonstrated
10
9
L
L
00
W=50%
0
0
88
8
9
3
a
0
O
0
0
O
O
U
J0
0
0
0
0 0
6
00
5
00
O
4 '
0
20
40
60
80 100
Time above MIC (%)
10
25
50 100
300
24-hour AUC/MIC ratio
'References 6,19,20,22-24,27,29,36,37,39,40,43,50,51.
0.1
1
81
FIGURE 1-to. Relationship between three pharmacodynamic parameters (percentage of time
serum levels are above minimum inhibitory concentration [MIC], the 24-hour area under the
concentration curve [AUC], and the Cm JMIC
ratio) and the number of Pseudomonas aeruoinosa organisms in the thighs of neutropenic mice
after 24 hours of therapy with meropenem. Each
point represents two mice (mean of four thighs).
The dotted line reflects the number of bacteria at
the initiation of therapy. The 02 value represents
the percentage of variation in bacterial numbers
that could be attributed to differences in each of
the individual pharmacodynamic parameters.
CFU, colony-forming unit
10
100
cmax/MIC ratio
1000
FIGURE 1-11. Relationship between three pharmacodynamic parameters (percentage of time serum
l evels are above minimum inhibitory concentration [MIC], the 24-hour area under the concentration
curve [AUC], and the C m./MIC ratio) and the number
of Streptococcus pneumoniae organisms in the
thighs of neutropenic mice after 24 hours of therapy
with levofloxacin. Each point represents one mouse
( mean of two thighs). The dotted line reflects the
number of bacteria at the initiation of therapy. The R 2
value represents the percentage of variation in bacterial numbers that could be attributed to differences
in each of the individual pharmacodynamic parameters. CFU, colony-forming unit.
Antimicrobial Pharmacokinetics and Pharmacodynamics 1 9
that the AUC and C. level are the most important dosing
parameters as long as the dosing interval is not extended
beyond the T >MIC and the postantibiotic effect. In these
studies the major contribution of higher peak concentrations was the prevention of regrowth of resistant subpopulations. 39,s4 Furthermore the toxicodynamics of the
aminoglycosides would also favor optimizing the C.
level." ,"-s8 The aminoglycoside uptake kinetics at both of
the end-organ sites of toxicity (renal tubule and organ of
Corti) are saturable. Experimental animal models and
human data have demonstrated that the renal cortical
uptake of aminoglycosides is less with once-daily dosing
than with more frequent administration (Figure 1-12). 59
Similar animal model data have also examined aminoglycoside kinetics in relation to ototoxicitys'
Although the glycopeptides, tetracyclines, azalides,
and azoles do not exhibit concentration-dependent
killing, the AUC/MIC ratio has been the major parameter
correlating with therapeutic efficacy of these drugs. 19,20,36
This parameter correlation is likely related to the prolonged PAEs produced by these drug classes. For example, Louie et al demonstrated that fluconazole efficacy in
a murine candidiasis model was dependent upon the total
dose of drug (AUC) and not the dosing interval. 60
Subsequent evaluation demonstrated prolonged in vivo
persistent effects (postantifungal effects) and confirmed
the importance of the AUC in describing the activity of
the azoles. 16
Antivirals
Pharmacodynamic analysis with antivirals has been more
difficult because of the lack of reproducible, standardized
in vitro susceptibility testing. Various studies, however,
have demonstrated the impact of dose and dosing interval
upon antiviral effect and drug toxicity. 61 Drusano et al
have successfully examined the effect of a variety of dosing intervals upon antiviral efficacy using an in vitro hollow fiber model. 61,62 For example, these investigations
250
200
150
100
50
0
qd bid CI
qd CI
qd CI
Amikacin Gentamicin Netilmicin
qd tid CI
Tobramycin
FIGURE 1-12. Renal cortical concentrations (mg/kg) of amikacin, gentamicin, netilmicin, and tobramycin following 24 hours of drug
administration by continuous infusion, once daily, twice daily, or
thrice daily. Cl, renal clearance. (From Urban A, Craig WA: Daily dosi ng of aminoglycosides. Curr Clin Top Infect Dis 1997;17:238-255.)
found the protease inhibitors are most efficacious when
administered by continuous infusion, suggesting that the
duration of time concentrations remain above a threshold
level may be the most important PK-PD determinant for
these compounds." ,' This same group of investigators
found a similar dosing strategy to be important for the
efficacy of zidovudine in a murine encephalitis model6 s
On the other hand, the nucleoside analog stavudine was
more efficacious when dosed intermittently in the hollow
fiber model. 66 Analysis of foscarnet dosing in two
cytomegalovirus retinitis clinical trials have demonstrated that both efficacy and toxicity are driven by total
drug exposure or the AUC . 67,61 Most recently, clinical
trial analysis has demonstrated that the time to clearance
of influenza is related to the AUC of the neuraminidase
inhibitor. 69
MAGNITUDE OF PHARMACOKINETICPHARMACODYNAMIC PARAMETER REQUIRED
FOR EFFICACY AND CLINICAL IMPLICATIONS
Because PK-PD parameters can correct for differences in
pharmacokinetics among species and intrinsic antimicrobial activity, it has been shown that the magnitude of
these parameters necessary for efficacy is similar in different animal species including humans.' 9,39,70-7a This
should not be surprising since the receptor for the antimicrobial is in the pathogen and therefore is the same in
both animal models and humans. Studies show that the
magnitude of the PK-PD parameter required for efficacy
of a drug is similar for different dosing regimens, for different drugs within the same class providing free drug
concentrations are used, and for different sites of infection. 19 Furthermore, treatment of infections due to
organisms with reduced susceptibility to penicillins,
macrolides, and quinolones and with resistance mechanisms due to reduced target affinity also appear to require
similar parameter magnitudes for efficacy. 10,73,74 Thus the
results from these studies in animal infection models
have been useful in the design of dosing regimens in
humans. 75,16 This has been particularly helpful for the
design of dosing regimens for antimicrobials under
development and also for those drugs already available in
clinical situations in which it is difficult to accumulate
sufficient patient data, as is the case for the treatment of
emerging resistant pathogens. Most recently this type of
analysis has been used in the development of antimicrobial treatment guidelines for otitis media, sinusitis, and
community-acquired pneumonia. 75,77-79
(3-Lactams
Studies in animal infection models and humans have
demonstrated that antibiotic concentrations do not need
to exceed the MIC for the entire dosing interval to
exert sufficient antimicrobial activity. 43, s0 For a variety
10 I Antimicrobial Pharmacokinetics and Pharmacodynamics
4
to
m
L3:
-v
LL
o`
U `r
2
O
o
0
00
O
00900 ® 0
0
®0
0
0
20
0
b'® (;~BD 0oo
40
60
aP 8
0
80
100
Time above MIC (% of dosing interval)
FIGURE 1-13. Relationship between time above minimum inhibitory
concentration (MIC) and change in bacterial number for numerous
strains of Streptococcus pneumoniae at 24 and 48 hours in the
thighs and lungs, respectively, of neutropenic mice following treatment with amoxicillin or amoxicillin-clavulanate. CFU, colony-forming unit. (From Andes D, Craig WA: In vivo activities of amoxicillin
and amoxicillin-clavulanate against Streptococcus pneumoniae:
Application to breakpoint determinations. Antimicrob Agents
Chemother 1998;42:2375-2379.)
of (3-lactams, in vivo bacteriostatic efficacy in animal
infection models has been observed when serum levels
are above the MIC for 20% to 40% of the dosing interval,
and maximal organism reductions are seen when levels
are above the MIC for 60% to 70% of the interval. 19,42,70,80
Similar times above the MIC have been observed for a
variety of (3-lactams in several infection models and at
several infection sites providing free drug levels in serum
were used for comparison. Data in Figure 1-13 represent
a compilation of two amoxicillin in vivo studies against
S. pneumoniae in a thigh and lung infection model .70 In
general, the percentages of time above the MIC are
slightly lower for the penicillins (30% to 40%) than for
the cephalosporins (40% to 50%) and are lower yet for the
carbapenems (20% to 30%). 19 These differences appear to
reflect differences in the rate of killing, which is fastest
with the carbapenems and slowest with the cephalosporins.
Drug kinetics in the central nervous system (CNS)
are different from those in any other compartment of
the body. The fluid surrounding the brain parenchyma
is an ultrafiltrate of serum. Despite these clear differences in kinetics, one would expect that the patterns of
antimicrobial activity predictive of efficacy outside of
the CNS would also be observed in meningitis.
However, the poor penetration of most antibiotics
across the blood-brain barrier and the long elimination
half-lives observed in cerebrospinal fluid (CSF) compared with those in serum often result in much less
fluctuation in drug concentrations than is observed in
other infection sites. Furthermore the goal of complete
sterilization in the CSF to prevent disease relapse is
with few exceptions not necessary in other infections.
In general, however, the pharmacodynamic activity and
relationships for the various classes of antimicrobials
do hold true in this protected site. 81-85 Here, however, it
is clear that CSF levels are a much stronger predictor of
efficacy than serum levels. In addition, because of the
significant differences in rates of organism replication in
the CSF and the lack of factors present in serum that can
often contribute to prolonged PAEs, the in vitro measure
with which drug kinetics are best correlated is the MBC
rather than the MIC. 83 For example, the (3-lactams in
serum saturate killing rates with levels exceeding the
MIC four or five times, whereas in the CSF maximum
bactericidal activity is not observed until levels exceed
the MBC by 10 to 30 times." Lutsar et al found maximal killing in a rabbit meningitis model when ceftriaxorie levels exceeded the MBC for 75% to 100% of the
dosing interval. 85 Likewise, study of ampicillin in
pneumococcal meningitis models fractionated into 8-,
12-, and 24-hour regimens showed it was successful as
long as CSF ampicillin levels exceeded the MBC for
about 50% of the dosing interval, similar to the relationship observed in nonmeningitis models. 79
Although studies in animal infection models lend
themselves to easily determining parameter magnitudes
necessary to achieve a variety of treatment endpoints,
there are obvious limitations to making similar observations in clinical trials. For prospective clinical trials there
is the ethical issue regarding the design of treatment regimens thought to be potentially inferior (R- lactam regimen with T >MIC less than 40% of dosing interval). For
retrospective analysis there may not be enough MIC
(pathogen resistance) or drug concentration variation to
produce sufficient parameter magnitude variations.
However, one clinical study type that is being recognized
as increasingly important for predicting pharmacodynamic outcomes in humans is the clinical trial simulation
using population pharmacokinetics. 86 These investigations determine antimicrobial pharmacokinetics in
patient populations representative of those who would
receive antimicrobial treatments in various clinical scenarios using optimal sampling techniques. Large clinical
trials of patients with varying pharmacokinetics are simulated to determine the frequency with which a specific
dosing regimen would achieve a pharmacodynamic target against most (e.g., MIC 90) of the pathogens one
would expect to encounter. This pharmacodynamic target
is based upon results from animal model studies. The
data from these studies is then related to the distribution
of MICs of the target pathogens. For example, (3-lactams
have been shown to be effective when dosing regimens
produced serum levels above the MIC for 40% to 50% of
the dosing interval.
A few clinical trial investigations have lent themselves to pharmacodynamic analysis. Several investigators have performed treatment trials in acute otitis media
in children and acute maxillary sinusitis in adults in
which fluid at the site of infection has been sampled
before and after antimicrobial therapy to determine bacteriologic cure rates. 72,a 7-92 Furthermore, because of the
Antimicrobial Pharmacokinetics and Pharmacodynamics I 11
emergence of resistant S. pneumoniae, recent studies of
this type have provided MIC fluctuation of sufficient
degree to produce pharmacodynamic magnitude variation. As one would expect, the primary therapeutic agents
used in these respiratory tract treatment trials have
included a variety of R-lactams and macrolide antibiotics.
One can estimate the time above MIC for the various
antimicrobial agents based upon human pharmacokinetic
data and the MICs of the organisms recovered and examine the relationship between bacteriologic treatment success and the magnitude of the T >MIC. In Figure 1-14
one sees bacteriologic cure rates in the range of 85% to
100% when R-lactam and macrolide serum levels
exceeded the MIC for 40% to 50% of the dosing interval.72 This is similar to the time above the MIC found to
produce bacteriologic efficacy of (i-lactam in animal
models. Ambrose et al observed a similar association in
the treatment of community-acquired pneumonia. 93 This
study of cefuroxime therapy compared continuous infusion of 1.5 g/day (T >MIC 100%) to a lower total dose
administered thrice daily (750 mg = T >MIC 50% to
60%) and found no difference in clinical endpoints.
These results suggest again that serum drug levels need
not exceed the MIC for the entire dosing interval and that
a T >MIC magnitude of 40% to 50% may be a suitable
target.
Continuous infusion is the most efficient approach for
achieving serum levels above the MIC of an infecting
organism. This regimen design can be convenient in the
outpatient setting because of the reduction in the number
of manipulations necessary. In addition, less total drug is
necessary to achieve the pharmacodynamic goal. Since
the rate and extent of killing with (3-lactams saturates at
concentrations around four times the MIC, one could
choose this as a target steady state concentration for continuous infusion dosing. One could estimate the dose and
rate of infusion with a simple calculation. One need only
consult a common reference book to find the estimated
volume of distribution and elimination half-life of the
100
80
U
U
. O)
O
0L
60
40
U 20
m
m
0 1
0
I
80
1J
100
Relationship between the time above minimum
i nhibitory concentration (MIC) and bacteriologic cure for various
P-lactams and macrolides against Streptococcus pneumoniae and
Haemophilus influenzae i n patients with otitis media and sinusitis.
FIGURE 1-14.
R - (Css) (VD) (BW)
(0 .693)
(t/O
Where R is the rate of infusion (mg/h), C', is the desired
steady state concentration (mg/L),
is the volume of
distribution (L/kg), BW is the body weight (kg), and tii2
is the elimination half life in hours. In addition to the
therapeutic advantage of continuous infusion, the ability
to use less total drug to achieve one's dosing goal may
also reduce the incidence of dose-related adverse effects
such as neutropenia. For example, a 2 g dose of ceftazidime administered every 8 hours would achieve a
steady state level of 25 mg/L. On the other hand, a 3 g
ceftazidime dose administered via continuous infusion
would achieve a level of 29 mg/L. 45,46 Continuous infusion is best suited for R-lactam drugs with short elimination half-lives and stability at room temperature for at
least 12 hours.
o
Macrolides
When one looks at various macrolide antibiotics, animal
infection models have suggested that efficacy is achieved
when serum levels are above the MIC for 50% of the dosing interva1. 19,2o As with a number of P-lactams,
macrolides have also been examined in double-tap otitis
media trials .12 Data in Figure 1-14 also include a number
of macrolide trials. As with P-lactams, when serum levels
of the macrolides exceeded the MIC 40% to 50% of the
dosing interval, high rates of bacteriologic eradication are
observed. For example, treatment against susceptible
S. pneumoniae was successful in 93% and 100% of
patients treated with erythromycin and clarithromycin,
respectively (Table 1-2). One would anticipate this high
success rate, with macrolide levels above the MIC for
much more than 50% of the dosing interval. On the other
hand, when examining treatment outcome against
Haemophilus influenzae one would anticipate bacteriologic failures, as macrolide dosing would achieve levels
above the MIC for far less than 50% of the dosing interval. In these trials, both erythromycin and clarithromycin
resulted in bacteriologic success rates similar to those
that would be observed with placebo (50% or less).
Azithromycin and Ketolides
O • Otitis media
D • Sinusitis
I
I
1
20
40
60
Time above MIC
drug. Factoring in the body weight of the patient, the rate
of infusion would equal (R):
For the azalide azithromycin and the new ketolide class
of antimicrobial, the 24-hour AUC/MIC ratios have correlated best with treatment outcome. The magnitude of
the azalide 24-hour AUC/MIC ratio associated with treatment efficacy in both in vivo infection models and
clinical trials is near 25. 2° The clinical trial data available
for azithromycin is similar to the otitis media data for
the (3-lactams and other macrolides. In treatment of
12 1 Antimicrobial Pharmacokinetics and Pharmacodynamics
TABLE 1-2 n
Bacteriologic Cure in Otitis Media with Macrolide Based upon
Pharmacodynamic Parameter Magnitude
Streptococcus pneumoniae
Drug
Susceptibility
Erythromycin
Clarithromycin
Azithromycin
S
S
S
R
Haemophilus influenzae
PK-PD Parameter
magnitude
Bacteriologic cure
T>MIC = 88%
T>MIC = 100%
AUC/MIC = 50
AUC/MIC < 0.1
14/15(93%)
12/12 (100%)
15/16(94%)
1/3(21%)
PK-PD Parameter
magnitude
Bacteriologic
cure
T>MIC = 0%
T>MIC = 0%
AUC/MIC < 2
3/2005%)
3/15(20%)
13/35(37%)
Susceptibility
R
S?
S?
AUC (area under the serum concentration-time curve)/MIC (minimum inhibitory concentration) ratio; PD, pharmacodynamic; PK, pharmacokinetic; R,
resistant; S, susceptible; T>MIC, percentage of time serum concentrations exceed the MIC.
azithromycin-susceptible S. pneumoniae, when the
24-hour AUC/MIC ratio exceeded 25, bacteriologic success was observed in 94% of patients (Table 1-2). In the
treatment of resistant S. pneumoniae and H. influenzae,
however, 24-hour AUC/MIC values are low (<O.1 and 2,
respectively), and treatment success rates were similar to
what one would expect from placebo alone (21% and
37%, respectively)." For treatment of pathogens in pneumonia, if ELF concentrations (24-hour AUC/MIC 25 =
MIC 2 gg/mL) are more important than serum pharmacodynamics (24-hour AUC/MIC 25 = MIC 0.12 gg/mL),
then one would predict being able to successfully treat
infections due to organisms with MICs 16-fold higher
than has been demonstrated in otitis media (Table 1-1). 10
Again, however, no studies thus far have answered this
important question. Similar 24-hour AUC/MIC magnitudes may apply to the ketolides.
Fluoroquinolones
Studies against gram-negative bacilli in animals and
humans have suggested that the fluoroquinolone 24-hour
AUC/MIC ratio must exceed 100 to 125 to obtain high
rates of bacteriologic efficacy and clinical cure. 16,24
Analyses from a variety of animal models including
pneumonia, endocarditis, meningitis, and thigh infection
demonstrate that the magnitude of the AUC/MIC ratio is
similar regardless of the infection site. 6,19,39,40,43 Data
shown in Figure 1-15 demonstrate maximal survival in a
variety of gram-negative in vivo infection models when
the 24-hour fluoroquinolone AUC/MIC ratio approaches
a value of 100. A 24-hour AUC/MIC ratio of near 100 is
essentially like maintaining serum concentrations four
times above the MIC during the 24-hour dosing period.
Forrest et al found a relationship between a ciprofloxacin
24-hour AUC/MIC ratio of greater than 125 and satisfactory clinical outcomes in an intensive care unit population (Fig. 1-16). 2 Lower parameter magnitudes resulted
in treatment failures in nearly 50% of patients. Preston et
al have also analyzed a clinical trial using levofloxacin
population pharmacokinetics and demonstrated that a
Cmax/MIC ratio of greater than 12 or a 24-hour
AUC/MIC ratio of 100 was predictive of treatment success. 86 However, studies using in vitro kinetic models,
100
O 00 O
°°
0
O
so
0 60
o®
O
O
0
00
O
40
O
20
O
069
00
9P0 0
00 4WO
30
100 300
10
24-hour AUCIMIC ratio
0
1000
FIGURE 1-15. Relationship between the 24-hour area under the concentration curve (AUC)/minimum inhibitory concentration (MIC)
ratio and mortality in various experimental infection models treated
with fluoroquinolones. Solid circles, data from neutropenic murine
thigh and lung infection models. Hollow circles, data from the literature using pneumonia, peritonitis, and sepsis models in mice, rats,
and guinea pigs. (From Craig WA, Dalhoff A: Pharmacodynamics of
fluoroquinolones in experimental animals. In Kuhlman J, Dalhoff A,
Zeiler HJ [eds]: Handbook of Experimental Pharmacology, vol 127:
Quinolone Antibacterial. pp 207-232.)
100
80
so
U
U
w
40
so
0
0-67.5
e2.5-125
125-250
250-SW
>5oo
24 hour AUCIMIC ratio
FIGURE 1-16. Relationship between the 24-hour area under the curve
( AUC)/minimum inhibitory concentration WIC) ratio and the
microbiologic and clinical efficacy of ciprofloxacin in patients
with serious bacterial infections. (From Craig WA: Pharmacokinetic/pharmacodynamic parameters: Rationale for antibacterial dosing of mice and men. Clin Infect Dis 1998;26:1-12.)
Antimicrobial Pharmacokinetics and Pharmacodynamics 1 13
animal survival studies in nonimmunocompromised
animals, and clinical trials suggest that the magnitude of
the 24-hour AUC/MIC ratio necessary for efficacy of the
quinolones in treatment of pneumococcal infections is
more in the range of 25 to 35, or essentially like having
levels average 1 time the MIC for the 24-hour dosing
period. 6, '3,9a For example, Lacy et al studied both levofloxacin and ciprofloxacin in an in vitro kinetic model
of S. pneumoniae and observed maximal organism killing
with quinolone AUC/MIC ratios of approximately 30. 9'
This is also supported by studies in non-neutropenic
pneumococcal infection models with a number of fluoroquinolones in which maximal survival has been observed
when the 24-hour AUC/MIC ratio magnitude approaches
25 to 30 (Fig. 1-17). More recently, Ambrose et al examined the relationship between the fluoroquinolone
AUC/MIC ratio and treatment outcomes in patients with
pneumococcal lower respiratory tract infections. In this
randomized, double-blind evaluation a fluoroquinolone
24-hour AUC/MIC ratio of 50 was associated with a 90%
probability of bacterial eradication. 96 This AUC/MIC
magnitude is similar to that seen in experimental models
and offers an explanation for the good efficacy of the
newer fluoroquinolones against S. pneumoniae.
Aminoglycosides
Several investigators have found a C m,,/MIC ratio of 8 to
10 in both in vitro and in vivo models to be associated
with efficacy and the prevention of the emergence of
resistant subpopulations 28,29, s 0,'4 Recent analysis of multiple aminoglycoside animal model studies found a strong
relationship between the AUC/MIC ratio and bacteriologic efficacy in meningifs. 12 In this analysis a maximal
reduction in bacterial numbers was observed when the
aminoglycoside AUC/MIC ratio exceeded 50. One clinical nosocomial pneumonia trial also reported a clinical
response rate (reduction in fever and leukocytosis) in
more than 90% of patients when the C.,, x/MIC ratio
reached 8 to 10.97 Of further interest is the fact that most
patients did not achieve this dosing goal with the empiric
100
80
60
0
40
20
0
0
1
2.5
5
10
0
q0 0 W0
25
50
100
24-hourAUC/MIC ratio
FIGURE 1-17. Relationship between the 24-hour area under the concentration curve (AUC)/minimum inhibitory concentration (MIC)
ratio and survival in the neutropenic murine thigh and lung infection
models infected with S. pneumoniaetreated with fluoroquinolones.
use of 5 mg/kg/day of the aminoglycoside. Moore et al
found a similar association between C maVMIC ratio and
survival in the treatment of bacteremia. 98 Once-daily
aminoglycoside administration is the most efficient and
reliable strategy to achieve high peak concentrations.
A number of other investigations have studied the impact
of dosing regimens on the efficacy of aminoglycosides in
clinical trials 99,10° The results of these studies have been
examined in 7 meta-analyses and suggest a small, nonsignificant trend toward better efficacy in 5 of 7 analyses
and a 26% reduction in nephrotoxicity in the largest
analysis with the once-daily administration of aminoglycosides. 41,101-107 Other clinical studies have demonstrated
that the onset of nephrotoxicity is delayed for several days
(3 vs. 7 days) when these drugs are administered oncedaily rather than in multiple-daily doses.""" However,
once-daily dosing may not be best in all situations.
Animal models of enterococcal endocarditis have demonstrated a more significant reduction in vegetation organism counts when aminoglycosides were administered in
multiple rather than single daily doses. 112
Oxazolidinones
Although the distribution of linezolid MICs have thus far
been narrow, animal model studies suggest that efficacy
with these compounds is observed when dosing regimens
achieve serum levels above the MIC for 50% of the dosing interval." The studied dosage regimen of this drug
provides serum levels above an MIC of 8 gg/mL for 50%
of the dosing interval and has proven effective in various
comparative clinical trials.
Fluconazole
Although in vitro susceptibility testing with antifungals has
only recently been standardized, data from a number of animal model studies and clinical trials suggest that triazole
MICs correlate reasonably well with treatment outcomes.
For fluconazole, study in animal models has found treatment success associated with 24-hour AUC/MIC ratios near
25 over a wide range of MICs. 36 This, 24-hour AUC/NIIC
ratio correlates closely with the dose-MIC relationship
recently established by the NCCLS (National Committee
for Clinical Laboratory Standards)."' As shown in
Table 1-3, a fluconazole dose of 200 mg/day would produce a 24-hour AUC/breakpoint MIC (8 gg/mL) ratio of
near 20. With dose escalation to 400 or 800 mg/day, a similar ratio would be seen at the susceptible-dose-dependent
breakpoints (16-32 pg/mL), again similar to the parameter
magnitude observed in animal infection models.
Flucytosine
Andes and van Ogtrop found maximal reduction in
Candida burden in the kidneys of mice when flucytosine
serum levels were above the MIC of the organism for
14 I Antimicrobial Phannacokinetics and Pharmacodynamics
TABLE 1-3 • Comparison of Fluconazole AUC/MIC Ratio to Results from Clinical
Trials
NCCLS
breakpoint (mg/L)
R >>-64
S-DD 16-32
S<- 8
Dose (mg/day)
AUC (mg/hr/L)
800
400-800
200
475
240-475
134
AUCBreakpoint
MIC ratio
7
15
17
Clinical success
54
86
81
AUC, area under the serum concentration-time curve; MIC, minimum inhibitory concentration; NCCLS, National
Committee for Clinical Laboratory Standards; R, resistant; S, susceptible; S-DD, susceptible-close-dependent breakpoints.
50% of the dosing interval." These studies, however,
included only a single pathogen. If, however, this parameter magnitude is relevant for other organisms, it would
suggest that we are currently overdosing this compound
with a narrow therapeutic window. Current administration of 100 to 150 mg/kg/day in four divided doses would
provide time above the MIC 90 of commonly treated
pathogens for more than 100% of the dosing interval,
even if the interval were to be doubled.
PHARMACODYNAMICS OF COMBINATION
ANTIMICROBIAL THERAPY
Combination therapy has been used to enhance the antimicrobial activity of two or more drugs whose activity together
is either additive or synergistic. In addition, various drug
combinations have also been used to reduce the emergence
of resistance to one or both of the compounds and to reduce
drug toxicity by occasionally allowing the administration of
lower doses of drugs with a narrow therapeutic index.
A large number of in vitro studies have used a variety
of techniques to examine the effects of different antimicrobial classes in combination. 91. 11¢ 116 Despite the extensive fund of pharmacodynamic knowledge available for
an antimicrobial used alone, however, few studies have
analyzed the in vivo pharmacodynamics of these agents
used in combination. Thomas et al suggested that adding
the AUC/MIC ratio of an aminoglycoside or fluoroquinolone to the AUC/MIC ratio of a (3-lactam was an
appropriate way to estimate their pharmacodynamic
activity in combination. 117 Mouton et al however,
recently demonstrated that the in vivo pharmacodynamics predictive of efficacy of R-lactams, aminoglycosides,
and fluoroquinolones when used in combination is similar to that predictive of efficacy when these compounds
are used alone."' Thus the PK-PD parameter and parameter magnitude predictive of efficacy for individual drugs
are class dependent when used in combination and are
similar to when they are used as single agents.
TREATMENT OF RESISTANT ORGANISMS
Studies with a number of antimicrobial classes against
multiply resistant pathogens have observed similar
treatment outcomes when dosing regimens are able to
produce pharmacodynamic parameter magnitudes equal
to those shown to be successful in the treatment of susceptible pathogens. For example, in vivo pharmacodynamic studies with amoxicillin and amoxicillinclavulanate against a large number of strains of S. pneumoniae, including strains classified as penicillinsusceptible, -intermediate, and -resistant, with
amoxicillin MICs varying 60-fold, demonstrated that
the magnitude of the T >MIC parameter required to
produce various microbiologic outcomes (static dose,
ED50-801 and mortality) was similar for all of the organisms
(Fig. 1-18).1° Maximal killing over 24 hours was observed
when serum levels remained above the MIC for 50% to
60% of the dosing interval for both susceptible and resistant S. pneumoniae. In subsequent studies involving a longer
course of therapy (4 days), 100% survival was achieved
when dosing resulted in serum levels above the MIC for at
least 40% of the dosing interval. Analysis of cefprozil therapy in this model has demonstrated similar results. 119
In the past 5 years the NCCLS has begun to review
susceptibility breakpoints for oral P-lactams. Various
types of data have been factored into breakpoint determi
nations, including the population distribution of organism
MICs, the activity of the antimicrobial in question against
organisms with known mechanisms of resistance, the
correlation of clinical outcome with susceptibility results,
and, more recently, pharmacodynamic predictions from
in vivo infection models.
In situations in which there is insufficient clinical
data with various compounds against less susceptible
pathogens such as R-lactam-resistant pneumococci, the
NCCLS is relying upon PK-PD parameter magnitudes
defined in animal infection models. 12° For example, a
pharmacodynamic template for (3-lactams can be based
upon a pharmacodynamic goal of maintaining serum levels above the MIC of the infecting pathogen for 40% of the
dosing interval. Thus susceptibility breakpoints (MICs)
for various antimicrobial-organism combinations can be
based upon the highest MIC that would produce levels
above the MIC for 40% of the dosing interval. Table 1-4
lists the current susceptibility breakpoints for a number of
oral and parenteral (3-lactams and the highest MIC for
which serum levels would still remain above the MIC
for 40% of a standard dosing regimen. One can see that
often times the current breakpoint MIC is lower than the
Antimicrobial Pharmacokinetics and Pharmacodynamics 115
100
R2 - 85%
20
0
0
20
40
80
Tlme above MIC %
80
100
FIGURE 1-18. Left Panel, Relationship between change in log,, colony-forming units (CFU) per/thigh over 24 hours and duration of time that
serum levels exceed the minimum inhibitory concentration WIC) following doses of 2, 7, and 20 mg/kg of amoxicillin every 8 hours and doses
of 7 mg/kg of amoxicillin-clavulanate every 8 hours. Each value represents the mean for two thighs. Right Panel, Relationship between mortality and duration of time that serum levels exceed the MIC following doses of amoxicillin at 2, 7, and 20 mg/kg and amoxicillin-clavulanate
at 7 mg/kg every 8 hours. Each value represents the mean for 5 mice. R 2, percentage of variation in bacterial numbers that could be attributed to differences in each of the pharmacodynamic parameters. (From Andes D, Craig WA: In vivo activities of amoxicillin and amoxicillinclavulanate against Streptococcus pneumoniae: Application to breakpoint determinations. Antimicrob Agents Chemother 1998;42:
2375-2379.)
TABLE 1-4 a Accepted and Pharmacodynamic in Vitro Susceptibility Breakpoint
of Selected R-Lactams
Drug-Dosing regimen
Susceptibility breakpoint
MIC (gg/mL)
Amoxicillin 500 mg PO tid (40 mg/kg)
Amoxicillin 1 g PO tid (80 mg/kg)
Cefaclor 500 mg PO tid
Cefuroxime 500 mg PO bid
Cefprozil 500 mg PO bid
Cefpodoxime 200 mg PO bid
Cefixime 400 mg PO bid
Loracarbef 400 mg PO bid
Penicillin G 2 MU IV qid
Ampicillin 1 g IV qid
Nafcillin 2 g IV qid
Ticarcillin-Clavulanate 3 g IV qid
Cefotaxime 1 g IV tid
Cefuroxime 0.75 g IV tid
Ceftriaxone 1 g IV qid
Cefepime 1 g IV bid
Meropenem 0.5 g IV tid
I mipenem 500 mg IV qid
2.0*
2.0*
1.0*
1.0*
1.0*
0.5*
<0.1
<0.1
1.0t
8.Ot
0.5"
0.5*
0.5*
0.5*
4.Ot
4.Ot
Pharmacodynamic breakpoint
MIC (gg/mL) (T>MIC 40%)
2.0
4.0
0.5
1.0
1.0
0.5
0.5
1.0
4.0
4.0
1.0
16
2.0
4.0
2.0
4.0
4.0
4.0
MIC, minimum inhibitory concentration; T>MIC, percentage of time serum levels remain above the MIC.
*Streptococcus pneumoniae.
'Staphylococcus aureus.
pharmacodynamic breakpoint, particularly for the parenteral agents. The susceptibility breakpoints for the
parenteral compounds are almost always lower because
that these values have been based upon the treatment of
meningitis, where higher serum levels would be necessary
to achieve adequate CSF levels. There are numerous case
reports of meningitis treatment failures to support these
breakpoints. 121,122 In most situations, however, these
breakpoints would be too high to guide therapy of nonCNS sites such as pneumonia. A number of clinical trials
in the literature have demonstrated successful outcomes
when these agents have been used to treat these less sus-
ceptible pathogens in community-acquired pneumonia.
Pallares et al were the first to address this issue. For a
cohort of more than 500 patients with severe communityacquired pneumonia receiving both penicillins and thirdgeneration cephalosporins, mortality rates were
independent of the susceptibility of the pathogen (Table
1-5). 123 Most recently Feiken et al examined risk for mortality in more than 4000 patients with bacteremic pneumococcal pneumonia. 114 In this large analysis
investigators were able to demonstrate a significant association between MIC elevation and mortality. As shown in
Table 1-6 however, it was not until the penicillin MIC
16 1 Antimicrobial Pharmacokinetics and Pharmacodynamics
TABLE 1-5 • Treatment Impact of Drug-Resistant
Pneumococci on Mortality in CommunityAcquired Pneumonia
Mortality/Patients in group (%)
Penicillin
MIC (gg/ml)
PenicillinlAmpicillin
CeftotaximelCeftriaxone
S =<-0.06
1 = 0.12-1.0
R = 2-4
24/12609)
4/14(24)
6/24(25)
32/127(25)
5/3305)
13/59(22)
I, penicillin-intermediate; MIC, minimum inhibitory concentration; R,
penicillin-resistant; S, penicillin susceptible.
is due to changes in drug target affinity. This would
include macrolide- and ketolide-resistant pathogens with
methylase mutations and fluoroquinolone mutations in
one of the gyrases. There has, however, been a general
resistance mechanism for which the degree of in vitro
resistance does not appear to predict the in vivo behavior.
Pneumococci exhibiting resistance due to an efflux
mechanism appear significantly more susceptible in vivo
than the in vitro MIC testing would suggest. 73,74 For
example, the magnitude of the AUC/MIC ratio required
to produce a net bacteriostatic effect was twofold to sevenfold less than that required for either the susceptible
organisms or those with altered ribosomal affinity (Table
Similarly, in studies with the a new fluoroquinolone against susceptible organisms and those resistant because of GyrA, ParC, or ParE, a similar PK-PD
parameter magnitude was required to achieve efficacy.73
Studies with organisms overexpressing efflux pumps,
however, were more susceptible than would be predicted.
The magnitude of the AUC/MIC ratio necessary to
achieve a bacteriostatic effect was twofold to fivefold
less than that required for either the susceptible organisms or those with altered gyrase enyzmes. The reason(s)
underlying this in vitro-in vivo differential with organisms expressing these efflux pumps remains unclear.
1-7).74
TABLE 1-6 w Risk for Mortality in Bacteremic
Pneumococcal Pneumonia Based upon
P-Lactam MIC
Drug MIC
Odds ratio (95% CI)
Penicillin G MIC >>-4.0
Penicillin G MIC = 2.0
Penicillin G MIC = 0.12-1.0
Penicillin G MIC <- 0.12
Cefotaxime MIC >- 2.0
Cefotaxime MIC = 1.0
Cefotaxime MIC <_ 1.0
7.1 (1.7-30)
0.7 (0.1-5.5)
1.0 (0.3-3.0)
Referent
5.9 (1.1-33)
1.5 (0.3-7.4)
Referent
CI, confidence interval; MIC, minimum inhibitory concentration.
reached 4 gg/mL and the cefotaxime MIC reached 2 gg/mL
that the risk of death increased. In both of these circumstances, one would have predicted treatment failure for
these patients, as dosing regimens would not produce the
pharmacodynamic goal of T >MIC of 40%. Re-evaluation
of susceptibility breakpoints for the parenteral (3-lactams in
the treatment of non-CNS infections is under consideration.
Animal model studies with numerous fluoroquinolones,
macrolides, and ketolides have likewise demonstrated that
the pharmacodynamic parameter magnitude required to
successfully treat infections due to pathogens with
reduced susceptibility is most often the same as that
needed against susceptible organisms .' 3 14 This has been
the case for all organisms whose mechanism of resistance
>
PHARMACODYNAMIC PARAMETER-AND
MAGNITUDE REQUIRED TO PREVENT THE
EMERGENCE OF RESISTANCE
Clearly a number of factors can contribute to the development or emergence of antimicrobial resistance, including the organism inoculum and the varying mutational
rates of different microbial species. 67,125,126 However,
there is also a clear association between antimicrobial
exposure and the selection or development of resistance.
A growing knowledge base from in vitro and animal
infection models has been used to examine the relationships between antimicrobial PK-PD parameters for different antimicrobials and the emergence and prevention
of resistant pathogens.
TABLE 1-7 • Bacteriostatic Dose and Corresponding AUC/MIC Ratio of New
Ketolide and Fluoroquinolone against Various Susceptible and
Resistant Streptococcus pneumoniae Strains
Drug
MIC (mg/L)
Resistance mechanism
Bacteriostatic dose
( mg/kg/day)
AUC/MIC ratio
Ketolide
0.015
0.06
0.5
0.008-0.015
0.06-0.5
0.06-0.12
Susceptible
Decreased affinity (MLS B)
Drug efflux (Mef)
Susceptible
GyrA, ParC, ParE
Efflux
8-20
73-96
145-153
112-781
224-1222
1 92035-286)
260-826
660-883
160-165
10-73
10-56
11 401-116)
Fluoroquinolone
AUC, area under the serum concentration time curve; MIC, minimum inhibitory concentration.
Antimicrobial Pharmacokinetics and Pharmacodynamics 1 17
Resistance Mutations
In most clinical trials and in vivo animal infection models, analysis demonstrating the relationship between
antimicrobial dosing and resistance mutations has been
extraordinarily difficult because of the relatively low
mutation rates. In a nosocomial pneumonia trial of
ciprofloxacin therapy, however, in those patients infected
with P. aeruginosa, six patients developed drug resistance during therapy. 121 In this small cohort of patients
who developed resistance the ciprofloxacin Cma~MIC
ratio was less than 8. In the group of four patients whose
C./MIC ratio exceeded 8, however, only one developed
resistance. Thomas et al similarly examined data from a
larger cohort of 107 patients with pneumonia."' In this
cohort, 25% of patients developed drug resistance. The
incidence of resistance was highest for P. aeruginosa and
(3-lactamase (type I)-producing gram-negative bacilli
(45% and 27%, respectively). The investigators calculated the 24-hour AUC/MIC ratios from patients' serum
concentrations and the organisms' MIC. The authors then
determined the relationship between the magnitude of the
24-hour AUC/MIC ratio and the development of resistance. They found that quinolone AUC/MIC ratios
exceeding 100 and C ma,/M1C ratios of greater than 8
were associated with the emergence of resistance in 9%
of cases, whereas resistance developed 82% of the time
when these ratios were less than 100 and 8, respectively.
It is not clear if the same magnitudes for the C./MIC
and 24-hour AUC/MIC ratios apply to gram-positive
cocci such as S. pneumoniae, as these studies had only a
single case of infection with this organism.
In vitro models have been more successful in detecting resistant mutants following exposure to varying drug
concentrations over time. 121,129 Several investigators have
explored the concept of a mutation prevention concentration (MPC), defined as the lowest drug concentration in
agar that prevents the growth of any colonies of resistant
mutants for different organisms and for different drugs. 126
For example, the MPC 90 for a variety of fluoroquinolones
against S. pneumoniae has varied from 4 to 8 times the
MIC 90. 130 One potential disadvantage of this testing system is that it only measures the effect of long-term exposure to a constant concentration and does not examine the
effect of shorter term exposures to similar or higher concentrations. Further studies are necessary to examine the
clinical relevance of these observations.
Selection of Resistant Mutants
Although it has been difficult for animal infection models
to examine the relationship between the time course of
antimicrobial exposure and the development of resistance
mutations, these models have been useful for describing
the relationship between antimicrobial pharmacodynamics and the selection of resistant subpopulations. For
example, several animal and in vitro studies have suggested that a C.,/MIC ratio of at least 8 to 10 can
significantly reduce the emergence of resistant subpopulations with fluoroquinolones and aminoglycosides. 28,39, s4
Spread of Resistant Mutants
Along with eradicating the infecting pathogen from the
site of infection, antimicrobial therapy for respiratory
infections must aim to prevent the selection of resistant
mutants, and be capable of minimizing the carriage of
resistant strains in the nasopharynx. 131 The ability to
achieve these pharmacologic goals depends to some
extent on the PK-PD characteristics of the antibiotic and
on the dosing regimen. For example, it has been theorized
that long half-life drugs that provide sustained but subMIC concentrations may be more likely to promote
selection of resistant pathogens.
Antibiotics vary in their ability to eradicate the
pathogen from the nasopharynx. Times above MIC
around 80% to 100% are required for (3-lactams to achieve
eradication, which is only possible at higher doses than
are currently used for most (3-lactams. Macrolides have
been shown to reduce colonization in some studies, but
more often macrolide therapy increases carrier statu5.33,106,132-134
For example, Ghaffar et al recently examined carriage of pneumococci in the nasopharynx of
children following therapy with the extra-strength formulation of amoxicillin-clavulanate and azithromycin. 13s
Both amoxicillin-clavulanate and azithromycin were successful in eradicating susceptible pneumococci (10/10
[100%] and 8/10 [80%], respectively). On the other hand,
amoxicillin-clavulanate eradicated intermediate and
resistant pneumococci in 82% (14/17) of patients,
whereas azithromycin therapy cleared resistant organisms
in only 36% (5/14) of patients. Overall amoxicillin-clavulanate was superior to azithromycin for eradicating the
pneumococcal carrier state (P = 0.04). The fluoroquinolones are generally effective at eradicating organisms from the nasopharynx.
Clearly much more information is needed to determine which PK-PD parameter and its magnitude that is
necessary to prevent the emergence of resistant organisms with commonly used antimicrobials.
SUMMARY
Pharmacokinetic and pharmacodynamic parameters are
the major determinants of the efficacy of antimicrobial
therapy. The ability of a drug to reach the magnitude of
the parameter required for efficacy against common
pathogens and emerging resistant organisms should be
considered in drug and dosage regimen selection for
empiric therapy (Table 1-8). Antimicrobial pharmacodynamic analyses have been useful for the development of
(1) in vitro susceptibility breakpoints, (2) antimicrobial
treatment guidelines, (3) new drug formulations (e.g.,
high-dose/ratio amoxicillin-clavulanate and extended
18 1 Antimicrobial Pharmacokinetics and Pharmacodynamics
TABLE 1-8 a Pharmacodynamic Activity of Antimicrobials
Pattern of activity
Pharmacodynamics
Drug class
Concentration dependent
Persistent effects
Parameter
Magnitude
Antibacterials
Penicillins
Cephalosporins
Carbapenems
Macrolides
Azithromycin
Oxazolidinones f inezolid)
Trimethoprim-Sulfamethoxazole
Clindamycin
Glycylcyclines
Fluoroquinolones
No
No
No
No
No
No
No
No
No
Yes
Minimal
Minimal
Minimal
Modest
Prolonged
Minimal
Minimal
Minimal
Modest
Prolonged
T>MIC
T>MIC
T>MIC
T>M I C
AUC/MIC
T>MIC
T>MIC
T>MIC
T>MIC
AUC/MIC
Aminoglycosides
Tetracyclines
Ketolides
Streptogramins (Synercid)
Daptomycin
Glycopeptides (vancomycin)
Metronidazole
Yes
No
Yes
No
Yes
No
Yes
Prolonged
Prolonged
Prolonged
Prolonged
Prolonged
Prolonged
Prolonged
Cman/MIC
AUC/MIC
AUC/MIC
AUC/MIC
AUC/MIC
AUC/MIC
Cmajmic
40%
50%
25%
40%-50%
25
40%
ND
ND
ND
25 (G +)
100 (G -)
8-10
ND
25-50
ND
ND
ND
ND
Antifungals
Triazoles
Polyenes
Flucytosine
Echinocandins
No
Yes
No
Yes
Prolonged
Prolonged
Modest
Prolonged
AUC/MIC
Cmejmlc
T>MIC
-
25
ND
25%-50%
-
Antivirals
Zidovudine (AZT)
Stavudine (D4T)
Protease inhibitors
Foscamet
Neuraminidase inhibitors
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
Time > Threshold
AUC/Threshold
Time > Threshold
AUC/Threshold
AUC/Threshold
ND
-ND
ND
ND
ND
AUC, area under the serum concentration-time curve; MIC, minimum inhibitory concentration; ND, no data; T>MIC, percentage of time serum concentration exceed the MIC.
release clarithromycin), and for (4) dose selection for
clinical trials.
7.
REFERENCES
2.
3.
4.
5.
6.
Fish DN, Gotfried MR, Danziger LH, Rodvold KA: Penetration
of clarithromycin into lung tissues from patients undergoing lung
resection. Antimicrob Agents Chemother 1994;38:876-878.
Forrest A, Nix DE, Ballow CH, et al: Pharmacodynamics of
intravenous ciprofloxacin in seriously ill patients. Antimicrob
Agents Chemother 1993;37:1073-1081.
Ryan DM, Hodges B, Spencer GR, Harding SM: Simultaneous
comparison of three methods for assessing ceftazidime penetration into extravascular fluid. Antimicrob Agents Chemother
1982;22:995-998.
Muller M, Stass H, Brunner M, et al: Penetration of moxifloxacin into peripheral compartments in humans. Antimicrob
Agents Chemother 1999;43:2345-2349.
Walstad RA, Hellum KB, Thurmann-Nielsen E, Dale LG:
Pharmacokinetics and tissue penetration of timentin: A
simultaneous study of serum, urine, lymph, suction blister,
and subcutaneous thread. J Antimicrob Chemother
1986;17(Suppl C):71-80.
Craig WA, DalhoffA: Pharmacodynamics of fluoroquinolones
in experimental animals. In Kuhlman J, Dalhoff A, Zeiler HJ
8.
9.
10.
11.
12.
13.
(eds): Handbook of Experimental Pharmacology, Vol 127.
Quinolone Antibacterials. Berlin, Springer-Verlag, 1998, pp
207-232.
Tulkens PM: Intracellular pharmacokinetics and localization of
antibiotics as predictors of their efficacy against intraphagocytic infections. Scand J Infect Dis 1990;74(Suppl):209-217.
Olsen KM, San Pedro G, Gann LP, et al: Intrapulmonary pharmacokinetics of azithromycin in healthy volunteers given five
oral doses. Antimicrob Agents Chemother 1996;40:2582-2585.
Patel KB, Xuan D, Tessier PR, et al: Comparison of bronchopulmonary pharmacokinetics of clarithromycin and azithromycin.
Antimicrob Agents Chemother 1996,40:2375-23 79.
Rodvold KA, Gotfried MH, Danziger LH, Servi RJ: Intrapulmonary steady-state concentrations of clarithromycin and
azithromycin in healthy adult volunteers. Antimicrob Agents
Chemother 1997;41:1399-1402.
Craig WA, Suh B: Protein binding and the antimicrobial
effects: Methods for the determination of protein binding. In
Lorian V (ed): Antibiotics in Laboratory Medicine, 4th ed.
Baltimore, Williams & Wilkins, 1996; pp 367-402.
Merrikin JJ, Briant J, Rolinson GN: Effect of protein binding
on antimicrobial activity in vivo. J Antimicrob Chemother
1983;11:233-238.
Kunin CM: Enhancement of antimicrobial activity of penicitlins
and other antibiotics in human serum by competitive serum
binding inhibitors. Proc Soc Exp Biol Med 1964;117:69-73.
Antimicrobial Pharmacokinetics and Pharmacodynamics 1 1 9
Andes D, Walker R, Ebert S, Craig WA: Increasing protein
binding of cefonicid enhances its in-vivo activity in an animal
model. 34th Interscience Conference on Antimicrobial Agents
and Chemotherapy, American Society for Microbiology, 1994.
Craig WA, Gudmundsson S: Postantibiotic effect. In Lorian V
(ed): Antibiotics in Laboratory Medicine, 4th ed. Baltimore,
Williams & Wilkins, 1996, pp 296-329.
16. Andes D, van Ogtrop ML: In vivo characterization of the pharmacodynamics of flucytosine in a neutropenic murine disseminated candidiasis model. Antimicrob Agents Chemother
2000;44:938-942.
17. Andes D, Van Ogtrop M, Craig WA: Pharmacodynamic activity of a new oxazolidinone in an animal infection model. 38th
Interscience Conference on Antimicrobial Agents and
Chemotherapy, American Society for Microbiology, 1998.
18. Craig WA, Andes D: Differences in the in vivo pharmacodynamics of telithromycin and azithromycin against Streptococcus
pneumoniae. In 40th Interscience Conference on Antimicrobial
Agents and Chemotherapy, American Society for Microbiology,
2000.
19. Craig WA: Pharmacokinetic/pharmacodynamic parameters:
Rationale for antibacterial dosing of mice and men. Clin Infect
Dis 1998;26:1-12.
20. Craig WA: Postantibiotic effects and the dosing of macrolides,
azalides, and streptogramins. In Zinner SH, Young LS, Acar
JF, Neu HC (eds): Expanding Indications for the New
Macrolides, Azalides and Streptogramins. New York, Marcel
Dekker, 1997; pp 27-38.
21. Klepser ME, Wolfe EJ, Jones RN, et al: Antifungal pharmacodynamic characterization of fluconazole and amphotericin B
tested against Candida albicans. Antimicrob Agents Chemother
1997;41:1392-1395.
22. Knudsen JD, Fuursted K, Raber S, et al: Pharmacodynamics of
glycopeptides in the mouse peritonitis model of Streptococcus
pneumoniae and StaphylocQecus aureus infection. Antimicrob
Agents Chemother 2000;44:1247-1254.
23. Leggett JE, Fantin B, Ebert S, et al: Comparative antibiotic doseeffect relations at several dosing intervals in murine pneumonitis and thigh-infection models. J Infect Dis 1989;159:281-292.
24. Leggett JE, Ebert S, Fantin B, Craig WA: Comparative doseeffect relations at several dosing intervals for beta-lactam,
aminoglycoside and quinolone antibiotics against gramnegative bacilli in murine thigh-infection and pneumonitis
models. Scand J Infect Dis Suppl 1991;74:179-184.
25. Vogelman B, Gudmundsson S, Tumidge J, Craig WA: The in
vivo postantibiotic effect in a thigh infection in neutropenic
mice. J Infect Dis 1988;157:287-298.
26. Eagle H, Musselman AD: The slow recovery of bacteria from
the toxic effects of penicillin. J Bacteriol 1949;58:475-490.
27. Andes D. In-vivo pharmacodynamics of amphotericin B
against Candida albicans. 39th Interscience Conference on
Antimicrobial Agents and Chemotherapy, American Society
for Microbiology, 1999.
28. Blaser J, Stone BB, Groner MC, et al: Comparative study with
enoxacin and netilmicin in a pharmacodynamic model to
determine importance of ratio of antibiotic peak concentration
to MIC for bactericidal activity and emergence of resistance.
Antimicrob Agents Chemother 1987;31:1054-1060.
29. Craig WA, Redington J, Ebert SC: Pharmacodynamics of
amikacin in-vitro and in mouse thigh and lung infections.
J Antimicrob Chemother, 1991;27(Suppl C):29-40.
30. Ernst EJ, Klepser ME, Pfaller MA: Postantifnngal effects of
echinocandin, azole, and polyene antifungal agents against
Candida albicans and Cryptococcus neoformans. Antimicrob
Agents Chemother 2000;44:1108-1111.
31. Safdar N, Andes D, Craig WA: In-vivo pharmacodynamic
characterization of daptomycin. 37th Annual Meeting of the
Infectious Diseases Society of America, 1999.
32. Cars O, Odenholt-Tomgvist I: The post-antibiotic sub-MIC
effect in vitro and in vivo. J Antimicrob Chemother
1993;31(Suppl D):159-166.
33. McDonald PJ, Wetherall BL, Pruul H: Postantibiotic leukocyte
enhancement: Increased susceptibility of bacteria pretreated
with antibiotics to activity of leukocytes. Rev Infect Dis
1981;3:38-44.
34. Odenholt-Tomgvist 1, Lowdin E, Cars O: Postantibiotic subMIC effects of vancomycin, roxithromycin, sparfloxacin, and
amikacin. Antimicrob Agents Chemother 1992;36:1852-1858.
35. Lorian V. Effect of low antibiotic concentrations on bacteria:
Effects on ultrastructure, virulence, and susceptibility to
immunodefenses. In Lorian V (ed): Antibiotics in Laboratory
Medicine, 4th ed. Baltimore, Williams & Wilkins, 1996,
pp 493-555.
36. Andes D, van Ogtrop M: Characterization and quantitation of
the pharmacodynamics of fluconazole in a neutropenic murine
disseminated candidiasis infection model. Antimicrob Agents
Chemother 1999;43:2116-2120.
37. Turnidge JD, Gudmundsson S, Vogelman B, Craig WA: The
postantibiotic effect of antifungal agents against common
pathogenic yeast. J Antimicrob Chemother 1994;34:83-92.
38. Craig WA, Ebert SC: Antimicrobial therapy in Pseudomonas
aeruginosa infection. In Baltch AL, and Smith RP (eds):
Pseudomonas aeruginosa Infections and Treatment. New
York, Marcel Dekker, 1994, pp 4411191.
39. Drusano GL, Johnson DE, Rosen M: Pharmacodynamics of a
fluoroquinolone antimicrobial agent in a neutropenic rat
model of Pseudomonas sepsis. Antimicrob Agents Chemother
1993;37:483-490.
40. Fantin B, Leggett J, Ebert S, Craig WA: Correlation between
in vitro and in vivo activity of antimicrobial agents against
gram-negative bacilli in a murine infection model. Antimicrob
Agents Chemother 1991;35:1413-1422.
41. Galloe AM, Gaudal N, Christensen HR, Kampmann JP:
Aminoglycosides: Single or multiple daily dosing? A metaanalysis on efficacy and safety. Eur J Clin Pharmacol
1995;48:39-43.
42. Craig WA: Interrelationship between pharmacokinetics and
pharmacodynamics in determining dosage regimens for
broad-spectrum cephalosporins. Diagn Microbiol Infect Dis
1995;21:1-8.
43. Vogelman B, Gudmundsson S, Leggett J, et al: Correlation of
antimicrobial pharmacokinetic parameters with therapeutic
efficacy in an animal model. J Infect Dis 1988;158:831-847.
44. Bodey GP, Ketchel SJ, Rodriguez N: A randomized study of
carbenicillin plus cefamandole or tobramycin in the treatment of febrile episodes in cancer patients. Am J Med
1979;67:608-616.
45. Houlihan HH, Mercier RC, McKinnon PS, et al: Continuous
infusion versus intermittent administration of ceftazidime in
critically ill patients with gram-negative infection (abstract 42,
p. 8). Abstracts of the 37th Interscience Conference on
Antimicrobial, Agents and Chemotherapy, American Society
for Microbiology, 1997.
46. Nenko AS, Cappelletty DM, Kruse JA, et al: Continuous infusion versus intermittent administration of ceftazidime in critically ill patients with suspected gram-negative infection.
[abstract A93, page 18]. In Abstracts of the 35th Interscience
Conference on Antimicrobial, Agents and Chemotherapy,
American Society for Microbiology, 1995.
47. Bakker-Woudenberg IAJM, van den Berg JC, Fontijne P, et al:
Efficacy of continuous versus intermittent administration of
penicillin G in Streptococcus pneumoniae pneumonia in nor
mal and immunodeficient rats. Eur J Clin Microbiol Infect Dis
1984;3:131-135.
48. Craig WA, and Ebert SC: Continuous infusion of (3-lactam
antibiotics. Antimicrob Agents Chemother 1992;36:2577-2583.
20 1 Antimicrobial Pharmacokinetics and Pharmacodynamics
49. Roosendaal R, Bakker-Woudenberg IA, van den Berg JC,
Michel MF: Therapeutic efficacy of continuous versus intermittent administration of ceftazidime in an experimental
Klebsiella pneumoniae pneumonia in rats. J Infect Dis
1985;152:373-378.
50. Gerber AU, Craig WA, Brugger HP, et al: Impact of dosing
intervals on activity of gentamicin and ticarcillin against
Pseudomonas aeruginosa in granulocytopenic mice. J Infect
Dis 1983;147:910-917.
51. Lustar I, Friedland IR, Wubbel L, et al: Pharmacodynamics of
gatifloxacin in cerebrospinal fluid in experimental
cephalosporin-resistant pneumococcal meningitis. Antimicrob
Agents Chemother 1998;42:2650-2655.
52. Pechere M, Letarte R, Pechere JC: Efficacy of different dosing
schedules of tobramycin for treating murine Klebsiella
pneumoniae bronchopneumonia. J Antimicrob Chemother
1987;19:487-494.
53. Powell S, Thompson W Luthe M, et al: Once-daily vs. continuous aminoglycoside dosing: Efficacy and toxicity in animals and clinical studies of gentamicin, netilmicin, and
tobramycin. J Infect Dis 1983;147:918-932.
54. Gerber AU, Vastola AP, Brandel J, Craig WA: Selection of
aminoglycoside resistant variants of Pseudomonas aeruginosa
in an in vivo model. J Infect Dis 1982; 146:691-697.
55. De Broe ME, Verbist L, Verpooten GA: Influence of dosage
schedule on renal cortical accumulation of amikacin and
tobramycin in man. J Antimicrob Chemother 1991;27
(Suppl C):41-47.
56. Giuliano RA, Verpooten GA, Verbist L, et al: In vivo uptake
kinetics of aminoglycosides in the kidney cortex of rats.
J Pharmacol Exp Ther 1986;236:470-175.
57. Tran BH, Deffrennes D: Aminoglycoside ototoxicity:
Influence of dosage regimen on drug uptake and correlation
between membrane binding and some clinical features. Acta
Otolaryngol (Stockholm) 1988;105:511-515.
58. Verpooten GA, Giuliano RA, Verbist L, et al: Once-daily dosing decreases renal accumulation of gentamicin and
netilmicin. Clin Pharmacol Ther 1989;45:22-27.
59. Urban A, Craig WA: Daily dosing of aminoglycosides. Curr
Clin Top Infect Dis 1997;17:236-255.
60. Louie A, Drusano GL, Banerjee P, et al: Pharmacodynamics of
fluconazole in a murine model of systemic candidiasis.
Antimicrob Agents Chemother 1998;42:1105-1109.
61. Drusano GL: Pharmacodynamics of antiretroviral chemotherapy. Infect Control Hosp Epidemiol 1993;14:530-536.
62. Drusano GL, Prichard M, Bilello PA, Bilello JA: Modeling
combinations of antiretroviral agents in vitro with integration
of pharmacokinetics: Guidance in regimen choice for clinical
trial evaluation. Antimicrob Agents Chemother 1996;
40:1143-1147.
63. Drusano GL, Bilello JA, Preston SL, et al: Hollow fiber unit
evaluation of BMS232632, a new HIV -1 protease inhibitor,
for the linked pharmacodynamic variable [abstract 1662,
p 339]. In Abstracts of the 40th Interscience Conference on
Antimicrobial Agents and Chemotherapy, American Society
for Microbiology, 2000.
64. Drusano GL, D'Argenio DZ, Preston SL, et al: Use of drug
effect interaction modeling with Monte Carlo simulation to
examine the impact of dosing interval on the projected antivi
ral activity of the combination of abacavir and amprenavir.
Antimicrob Agents Chemother 2000;44:1655-1659.
65. Bilello JA, Eiseman JL, Standiford HC, Drusano GL: Impact
of dosing schedule upon suppression of a retrovirus in a
murine model of AIDS encephalopathy. Antimicrob Agents
Chemother 1994;38:628-631.
66. Bilello JA, Bauer G, Dudley MN, et al: Effect of 2,3didehydro-3-deoxythymidine in an in-vitro hollow-fiber
pharmacodynamic model system correlates with results of
dose-ranging clinical studies. Antimicrob Agents Chemother,
1994;38:1386-1391.
67. Drusano GL, Aweeka F, Gambertoglio J, et al: Relationship
between foscarnet exposure, baseline cytomegalovirus (CMV)
blood culture and the time to progression of CMV retinitis in
HIV positive patients. AIDS 1996;10:1113-1119.
68. Drusano GL, Preston SL, Berman A, et al: Relationship
between foscarnet exposure and nephrotoxicity during induction therapy for CMV retinitis (abstract 499). Second National
Conference on Human Retroviruses and Related Infections,
Washington, DC, 1995.
69. Drusano GL, Treanor H, Fowler C, et al: Time to viral clearance after experimental infection with influenza A or B is
related to baseline viral titer and the plasma area under the
curve of RWJ-270201 (abstract 1391, p 29). In Abstracts of
the 40th Interscience Conference on Antimicrobial Agents
and Chemotherapy, American Society for Microbiology,
2000.
70. Andes D, Craig WA: In vivo activities of amoxicillin and
amoxicillin-clavulanate against Streptococcus pneumoniae:
Application to breakpoint determinations. Antimicrob Agents
Chemother 1998;42:2375-2379.
71. Andes DR, Craig WA: Pharmacodynamics of fluoroquinolones in experimental models of endocarditis. Clin Infect
Dis 1998;27:47-50.
72. Craig WA, Andes D: Pharmacokinetics and pharmacodynamics of antibiotics in otitis media. Pediatr Infect Dis J
1996;15:255-259.
73. Andes D, Craig WA: Pharmacodynamics of gemifloxacin
against quinolone-resistant strains of Streptococcus pneumoniae with known resistance mechanisms. 39th Interscience
Conference on Antimicrobial Agents and Chemotherapy,
American Society for Microbiology, 1999.
74. Craig WA, Andes DR: Impact of macrolide-resistance on the
in-vivo activity of ABT 773 on Streptococcus pneumoniae.
40th Interscience Conference on Antimicrobial Agents and
Chemotherapy, American Society for Microbiology, 2000.
75. Dowell SF, Butler JC, Giebink GS, et al: Acute otitis media:
Management and surveillance in an era of pneumococcal
resistance-a report from the drug-resistant Streptococcus
pneumoniae therapeutic working group. Pediatr Infect Dis J
1999;18:1-9.
76. Sinus and Allergy Health Partnership: Antimicrobial treatment
guidelines for acute bacterial rhinosinusitis. Otolaryngol Head
Neck Surg, 2000;123(Suppl 1):1-32.
77. Bartlett JG, Dowell SF, Mandell LA, et al: Practice guidelines
for the management of community-acquired pneumonia in
adults. Clin Infect Dis 2000;31:347-382.
78. Heffelflnger JD, Dowell SF, Jorgensen JH, et al: Management
of community-acquired pneumonia in the era of pneumococcal resistance. Arch Intern Med 2000;160:1399-1408.
79. Scheld WM, Sande MA: Bactericidal versus bacteriostatic
antibiotic therapy of experimental pneumococcal meningitis
in rabbits. J Clin Invest 1983;71:411-419.
80. Craig WA, Ebert S, Watanabe Y. Differences in time above
MIC required for efficacy of beta-lactams in animal infection
models (abstract 86). In Abstracts of the 33rd Interscience
Conference on Antimicrobial Agents and Chemotherapy.
American Society of Microbiology, 1993.
81. Craig WA: Does the dose matter? Clin Infect Dis
2001;33(Suppl 3):5233-5237.
82. Andes DR, Craig WA: Pharmacokinetics and pharmacodynamics of antibiotics in meningitis. Infect Dis Clinics N Am
1999;13:595-618.
83. Tauber MG, Zak O, Scheld WM, et al: The postantibiotic
effect in the treatment of experimental meningitis caused
by Streptococcus pneumoniae in rabbits. J Infect Dis
1984;149:575-583.
Antimicrobial Pharmacokinetics and Pharmacodynamics 1 2 1
84. Tauber MG, Doroshow CA, Hackbarth CJ, et al:
Antibacterial activity of (3-lactam antibiotics in experimental meningitis due to Streptococcus pneumoniae. J Infect
Dis 1984;149:575-583.
85. Lutsar I, McCracken GH, Friedland IA: Antibiotic
pharmacodynamics in cerebrospinal fluid. Clin Infect Dis
1998;27:1117-1129.
86. Preston SL, Drusano GL, Berman AL, et al: Pharmacodynamics of levofloxacin: A new paradigm for early clinical
trials. JAMA 1998;279:125-129.
87. Dagan R, Abramason O, Leibovitz E, et al: Bacteriologic
response to oral cephalosporins: Are established susceptibility breakpoints appropriate in the case of acute otitis media?
J Infect Dis 1997;176:1253-1259.
88. Dagan R, Leibovitz E, Fliss DM, et al: Bacteriologic efficacies of oral azithromycin and oral cefaclor in treatment of
acute otitis media in infants and young children. Antimicrob
Agents Chemother 2000;44:43-50.
89. Gwaltney JM, Savolainen S, Rivas P, et al: Comparative
effectiveness and safety of cefdinir and amoxicillinclavulanate in treatment of acute community-acquired bacterial sinusitis. Antimicrob Agents Chemother 1997;
41:1517-1520.
90. Scheld WM, Sydnor A, Farr B, et al: Comparison of
cyclacillin and amoxicillin for therapy for acute maxillary
sinusitis. Antimicrob Agents Chemother 1986;30:350-353.
91. Schentag JJ, Strenkoski-Nix LC, Nix DE, Forrest A:
Pharmacodynamic interactions of antibiotics alone and in
combination. Clin Infect Dis 1998;27:40-46.
92. Sydnor A, Gwaltney JM, Cocchetto DM, Scheld WM:
Comparative evaluation of cefuroxime axetil and cefaclor for
treatment of acute bacterial maxillary sinusitis. Arch
Otolaryngol Head Neck Surg 1989;115:1430-1433.
93. Ambrose PG, Quintiliani R, Nightingale CH, et al:
Continuous vs intermittent infusion of cef iroxime for the
treatment of community-acquired pneumonia. Infect Dis Clin
Prac 1997;7:463-470.
94. Lister PD, Sanders CC: Pharmacodynamics of levofloxacin
and ciprofloxacin against Streptococcus pneumoniae.
J Antimicrob Chemother 1999;43:79-86.
95. Lacy MK, Lu W, Xu X, et al: Pharmacodynamic comparisons
of levofloxacin, ciprofloxacin, and ampicillin against
Streptococcus pneumoniae in an in vitro model of infection.
Antimicrob Agents Chemother 1999;43:672-677.
96. Ambrose PG, Grasella DM, Grasela TH, et al:
Pharmacodynamics of fluoroquinolones against Streptococcus
pneumoniae: Analysis of phase-III clinical trials (abstract 1387,
p 28). In Programs and Abstracts from the 40th Interscience
Conference on Antimicrobial Agents and Chemotherapy,
American Society for Microbiology, 2000.
97. Kashuba AD, Nafziger AN, Drusano GL, Bertino JS:
Optimizing aminoglycoside therapy for nosocomial pneumonia caused by gram-negative bacteria. Antimicrob Agents
Chemother 1999;43:623-629.
98. Moore RD, Smith CR, Lietman PS: The association of
aminoglycoside plasma levels with mortality in patients with
gram-negative bacteremia. J Infect Dis 1984;149:443-448.
99. Deziel-Evans LM, Murphy JE, Job ML: Correlation of
pharmacokinetic indices with therapeutic outcome in
patients receiving aminoglycosides. Clin Pharm
1986;5:319-324.
100. Moore RD, Lietman PS, Smith CR: Clinical response to
aminoglycoside therapy: Importance of the ratio of peak concentration to minimal inhibitory concentration. J Infect Dis
1987;155:93-99.
101. Ali MZ, Goetz MB: A meta-analysis of the relative efficacy
and toxicity of single daily dosing versus multiple daily dosing of aminoglycosides. Clin Infect Dis 1997;24:796-809.
102. Bailey TC, Little JR, Littenberg B, et al: A meta-analysis of
extended-interval dosing versus multiple daily dosing of
aminoglycosides. Clin Infect Dis 1997;24:786-795.
103. Barza M, Ioannidis JPA, Cappelleri JC, Lau J: Single or multiple daily doses of aminoglycosides: A meta-analysis. BMJ
1996;312:338-345.
104. Ferriols-Lisart R, Alos-Alminana M: Effectiveness and
safety of once-daily aminoglycosides: A meta-analysis. Am J
Health Systems Pharm 1996;53:1141-1150.
105. Hatala R, Dinh T, Cook DJ: Once-daily aminoglycoside dosing in immunocompetent adults: A meta-analysis. Ann Intern
Med 1996;124:717-725.
106. Hatala R, Dinh TT, Cook DJ: Single daily dosing of aminoglycosides in immunocompromised adults: A systematic
review. Clin Infect Dis 1997;24:810-815.
107. Munckhof WJ, Grayson JL, Tumidge JD: A meta-analysis of
studies on the safety and efficacy of aminoglycosides given
either once daily or as divided doses. J Antimicrob
Chemother 1996;37:645-663.
108. Mailer R, Ahrne H, Holmen C, et al: Once-versus twicedaily amikacin regimen: Efficacy and safety in systemic
gram-negative infections. J Antimicrob Chemother
1993;31:939-948.
109. Nordstrom L, Ringberg H, Cronberg S, et al: Does administration of an aminoglycoside in a single-daily dose affect
its efficacy and toxicity? J Antimicrob Chemother
1990;25:159-173.
110. Prins JM, Buller HR, Kuijper EJ, et al: Once-versus thricedaily gentamicin in patients with serious infections. Lancet
1993;341:335-339.
111. Rybak MJ, Abate BJ, Kang SL, et al: Prospective evaluation
of the effect of an aminoglycoside dosing regimen on rates of
observed nephrotoxicity and ototoxicity. Antimicrob Agents
Chemother 1999;43:1549-1555.
112. Fantin B, Carbon C: Importance of the aminoglycoside dosing
regimen in the penicillin-netilmicin combination for treatment
of Enterococcus faecalis-induced experimental endocarditis.
Antimicrob Agents Chemother 1990;34:2387-2391.
113. Rex JH, Pfaller MA, Galgiani JN, et al: for the NCCLS
Subcommittee on Antifungal Susceptibility Testing:
Development of interpretive breakpoints for Antfungal sus
ceptibility testing: Conceptual framework and analysis of in
vitro-in vivo correlation data for fluconazole, itraconazole,
and Candida infections. Clin Infect Dis 1997;24:235-247.
114. Bustamante CL, Wharton RC, Wade JC: Iii vitro activity of
ciprofloxacin in combination with ceftazidime, aztreonam, and
azlocillin against multiresistant isolates of Pseudomonas aeruginosa. Antimicrob Agents Chemother 1990;34:1814-1815.
115. Hallender HO, Dornbusch K, Gezelius L, et al: Synergism
between aminoglycosides and cephalosporins with
antipseudomonal activity: Interaction index and killing curve
method. Antimicrob Agents Chemother 1982;22:743-752.
116. White RL, Burgess DS, Manduru M, Bosso JA: Comparison
of three different in vitro methods of detecting synergy:
Time-kill, checkerboard, and E test. Antimicrob Agents
Chemother 1996;40:1914-1918.
117. Thomas JK, Forrest A, Bhavnani SM, et al: Pharmacodynamic
evaluation of factors associated with the development of bacterial resistance in acutely ill patients during therapy.
Antimicrob Agents Chemother 1998;42:521-527.
118. Mouton JW, van Ogtrop ML, Andes D, Craig WA: Use of
pharmacodynamic indices to predict efficacy of combination therapy in vivo. Antimicrob Agents Chemother
1999;43:2473-2478.
119. Nicolau DP, Onyeji CO, Zhong M, et al: Pharmacodynamic
assessment of cefprozil against Streptococcus pneumoniae:
Implications for breakpoint determinations. Antimicrob
Agents Chemother 2000;44:1291-1295.
22 1 Antimicrobial Pharmacokinetics and Pharmacodynamics
120. National Committee for Clinical Laboratory Standards:
Development of in-vitro susceptibility testing criteria and
quality control parameters: Approved guideline, 2nd ed.
Document M23-A2. The Committee, Jan 2000.
121. Friedland 1R, Shelton S, Paris M, et al: Dilemmas in diagnosis
and management of cephalosporin-resistant Streptococcus
pneumoniae meningitis. Pediatr Infect Dis J 1993;12:196-200.
122. Kleiman MD, Wienbery GA, Reynolds JK, Allen SD:
Meningitis with beta-lactam resistant Streptococcus pneumoniae: The need for early repeat lumber puncture. Pediatr
Infect Dis J 1993;12:782-784.
123. Pallares R, Linares J, Vadillo M, et al: Resistance to penicillin and cephalosporin and mortality from severe pneumococcal pneumonia in Barcelona, Spain. N Engl J Med
1995;333:474-480.
124. Feikin DR, Schuchat A, Kolczak M, et al: Mortality from invasive pneumococcal pneumonia in the era of antibiotic resistance, 1995-1997. Am J Public Health 2000;90:223-229.
125. Fish DN, Piscitelli SC, Danziger LH: Development of resistance during antimicrobial therapy: A review of antibiotic
class and patient characteristics in 173 studies. Pharmacotherapy 1995;15:279-291.
126. Martinez JL, Baquero F: Mutation frequencies and antibiotic
resistance. Antimicrob Agents Chemother 2000;44:1771-1777.
127. Peloquin CA, Cumbo TJ, Nix DE, et al: Evaluation of intravenous ciprofloxacin in patients with nosocomial lower respiratory tract infections. Arch Intern Med 1989;149:2269-2273.
128. Peterson ML, Hovde LB, Wright DH, et al: Fluoroquinolone
resistance in Bacteroides fragilis following sparfloxacin exposure. Antimicrob Agents Chemother 1999;43:2251-2255.
129. Wu YL, Scott EM, Po AL, Tariq VN: Development of resistance and cross-resistance in Pseudomonas aeruginosa
exposed to subinhibitory antibiotic concentrations. APMIS
1999;107:585-592.
130. Blondeau JM, Zhao X, Hansen G, et al: Mutant prevention
concentrations of fluoroquinolones for clinical isolates of
Streptococcus pneumoniae. Antimicrob Agents Chemother
2001;45:433-438.
131. Schrag SJ, Beall B, Dowell SF: Limiting the spread of resistant pneumococci: Biological and epidemiologic evidence for
the effectiveness of alternative interventions. Clin Microbiol
Rev 2000;13:588-601.
132. Jackson M, Burry V, Olson L, et al: Breakthrough sepsis in
macrolide resistant pneumococcal infection. Pediatr Infect
Dis J 1996;15:1049-1051.
133. Morita JY, Kahn E, Thompson T, et al: Impact of
azithromycin on oropharyngeal carriage of group A
Streptococcus and nasopharyngeal carriage of macrolideresistant Streptococcus. Pediatr Infect Dis J 2000;19:41-46.
134. Leach A, Shelgy-James T, Mayo M, et al: A prospective study
of the impact of community-based azithromycin treatment of
trachoma on carriage and resistance of Streptococcus pneumoniae. Clin Infect Dis 1997;24:356-362.
135. Ghaffar FA, Katz K, Muniz LS, et al: Effect of amoxicillinclavulanate 14:1 vs. azithromycin on nasopharyngeal carriage and resistance of S. pneumoniae (abstract 98). In
Abstracts of the Infectious Diseases Society of America 38th
Annual Meeting, 2000.